Docker image built to run code, all evals run using R2RHEADmaster

1 files changed, 289 insertions, 0 deletions

diff --git a/gnqa/paper2_eval/data/dataset/gpt4o/gpt4o_cs_gn.json b/gnqa/paper2_eval/data/dataset/gpt4o/gpt4o_cs_gn.json
new file mode 100644
index 0000000..7c5bec1
--- /dev/null
+++ b/gnqa/paper2_eval/data/dataset/gpt4o/gpt4o_cs_gn.json
@@ -0,0 +1,289 @@
+{
+  "question": [
+    "What is GeneNetwork.org, and how does it help scientists understand genetics?",
+    "How do researchers use GeneNetwork.org to study diseases?",
+    "What can GeneNetwork.org tell us about how genes interact with each other?",
+    "How does GeneNetwork.org help in finding the genetic causes of common diseases?",
+    "Can GeneNetwork.org predict my risk of developing certain health conditions based on my genes?",
+    "How does GeneNetwork.org make use of data from different populations around the world?",
+    "What kinds of genetic data are available on GeneNetwork.org?",
+    "How do scientists use GeneNetwork.org to study differences in gene expression?",
+    "Can GeneNetwork.org be used to learn about genetic influences on behavior?",
+    "What role does GeneNetwork.org play in personalized medicine?",
+    "How does the information on GeneNetwork.org help in developing new treatments for diseases?",
+    "What is a gene network, and why is it important for understanding genetics?",
+    "How do researchers identify which genes are important for certain traits using GeneNetwork.org?",
+    "How can GeneNetwork.org help in understanding complex traits like height or intelligence?",
+    "Are there any known genetic mutations that cause premature aging?",
+    "What are the practical applications of the research done through GeneNetwork.org?",
+    "How can I access and use the data available on GeneNetwork.org?",
+    "What are some recent discoveries made using GeneNetwork.org?",
+    "How do scientists ensure the accuracy of the data on GeneNetwork.org?",
+    "What\u2019s the difference between looking at one gene and studying a whole gene network?"
+  ],
+  "answer": [
+    "GeneNetwork.org is a web service for systems genetics that started in 2001 as WebQTL, an online version of Ken Manly's Map Manager QT program [3]. It serves as a depository of datasets and tools for use in complex systems biology approaches to generate or predict higher-order gene function [8]. GeneNetwork.org is an open-access database that collates genomic information from diverse experimental crosses and reference panels, as well as phenotypic data from various research groups [9].  GeneNetwork.org helps scientists understand genetics by providing a platform for systems genetics, which involves the study of complex traits through the integration of networks of genes, transcripts, and traits such as toxicity, cancer susceptibility, and behavior across several species [10]. It offers tools for correlation and mapping strategies to assess associations among multiple genes and quantitative trait loci (QTLs), making the study of complex traits widely available to the scientific community [2]. Additionally, it supports predictive medicine and systems genetics by constantly being maintained and improved with data from multiple species and multi-omics analysis [1].",
+    "Researchers use GeneNetwork.org to study diseases by leveraging its capabilities as a bioinformatics tool for systems genetics analysis. This platform allows researchers to explore large phenotype and genome datasets from multiple species, which are essential for understanding complex biological networks and predicting molecular interactions [4], [5].   GeneNetwork.org supports a systems genetics approach, which examines how diverse sets of genetic and molecular markers contribute to phenotypes and diseases, rather than focusing on single gene mutations [2]. This approach is facilitated by the extensive data available on the platform, including gene expression patterns and drug response data, which can be compared and analyzed statistically [4].  The platform also enables correlation and network analysis, allowing researchers to compare associations between tissues and across different species, such as rodents and humans [6]. By studying networks of genes, proteins, metabolites, and other biomarkers, researchers can model genuine biological pathways, which helps in uncovering disease genes and understanding complex diseases [9].   Overall, GeneNetwork.org provides a comprehensive resource for predictive medicine and systems genetics, aiding researchers in constructing biological networks that are predictive of disease outcomes [1], [5].",
+    "GeneNetwork.org provides several tools and resources to explore how genes interact with each other. It is a bioinformatics tool that allows users to explore systems genetics data, which is crucial for defining biological networks and predicting molecular interactions [1]. GeneNetwork offers correlation and mapping strategies to assess associations among multiple genes and quantitative trait loci (QTLs), facilitating the study of complex traits [3]. Additionally, it provides access to a wide variety of data, including genotypes and phenotypes, which can illuminate relationships between different levels of a biological system, such as the genome, transcriptome, and phenome [6]. GeneNetwork also computes gene-gene co-expression correlations, which are essential for understanding gene interactions [9].",
+    "GeneNetwork.org aids in finding the genetic causes of common diseases by utilizing a systems genetics approach. This approach allows researchers to explore which phenotypes and diseases result from diverse sets of genetic and molecular markers, rather than focusing on single gene mutations [1]. GeneNetwork provides access to a wide variety of data, including genotypes (e.g., SNPs) and phenotypes, which can be used to study complex traits [7]. The platform integrates data on gene expression, protein interactions, and DNA-protein binding to construct biological networks that are predictive of disease [4]. Additionally, GeneNetwork offers correlation and mapping strategies for assessing associations among multiple genes and quantitative trait loci (QTLs), facilitating the study of complex traits [5]. This makes GeneNetwork a powerful tool for predictive medicine and systems genetics, helping researchers understand the genetic underpinnings of common diseases [6].",
+    "The context provided does not specifically mention GeneNetwork.org or its capabilities in predicting health conditions based on genetic information. However, the context does discuss the general potential of genetic information to predict disease risk. For example, it mentions the ability to identify individuals at higher genetic risk for common diseases [1], and the potential for genomic profiling to measure susceptibility to diseases [10].   While these references indicate that genetic information can be used to assess disease risk, there is no direct mention of GeneNetwork.org's specific capabilities in this area. Therefore, based on the provided context, it is unclear if GeneNetwork.org itself offers such predictive services.",
+    "GeneNetwork.org utilizes data from different populations around the world by integrating diverse genomic information and phenotypic data from various experimental crosses and reference panels. This allows for comprehensive exploratory and statistical analysis of large published phenotype and genome datasets [3], [4]. The platform includes data from multiple species, which facilitates the comparison of gene expression patterns with drug responses and other phenotypic traits [3]. Additionally, GeneNetwork.org provides analytical tools that enable users to compare traits across datasets from different experimenters, further enhancing the ability to study correlations and perform data mining in genomic regions [5], [9]. This integration of diverse datasets supports the construction of predictive biological networks by interfacing DNA variation data with gene expression, protein interactions, and DNA-protein binding information [6].",
+    "GeneNetwork.org provides a variety of genetic data, including:  1. Genomic information from diverse experimental crosses and reference panels, as well as phenotypic data from various research groups [3]. 2. Genetic variants such as SNPs (single nucleotide polymorphisms), insertions, deletions, and duplications [4]. 3. Extensive phenotype data extracted from the literature and submitted by users, which allows for comparisons of drug responses with gene expression patterns [5]. 4. Microarray data of gene expression in the brain and data of other phenotypes [8]. 5. Genotypes, including SNPs, and phenotypes obtained from various studies [10].  These datasets are designed to support systems genetics research and include data from multiple species [2], [5].",
+    "Scientists use GeneNetwork.org to study differences in gene expression by leveraging a variety of analytical tools and datasets available on the platform. GeneNetwork provides access to large published phenotype and genome datasets from several species, allowing for exploratory and statistical analysis [2]. The platform includes microarray data of gene expression in the brain and other phenotypes, which can be used to compare traits across different datasets [1].   GeneNetwork also facilitates the comparison of gene expression patterns with drug responses and other phenotypic data, making it practical for identifying candidate genes for complex traits through QTL analyses [2], [4]. The platform supports correlation and network analysis to compare associations between tissues and across rodent or human datasets, which is useful for systems genetics mapping [5].   Additionally, bioinformatic analyses on GeneNetwork.org include tools for gene ontology, presence of cis-regulation or polymorphisms, phenotype correlations, and principal component analyses, which help in evaluating differentially expressed genes and understanding distinct biological processes [10].",
+    "Yes, GeneNetwork.org can be used to learn about genetic influences on behavior. It is a comprehensive resource equipped with tools and features for studying genetic correlates to neurobehavioral phenotypes [5]. The platform includes a phenotype database with data on behavioral traits, among others, which can be used for correlation and network analyses to identify relationships with genetic data [4]. Additionally, GeneNetwork focuses on correlations of behavioral phenotypes with gene expression levels in recombinant inbred and inbred panels of mice and rats, which helps in identifying candidate genes for complex traits [6]. The resource is designed for the multivariate genetic analysis of complex traits, including behavior, in genetic reference populations [9].",
+    "GeneNetwork.org plays a significant role in personalized medicine by serving as an open-access, online data analysis resource for systems biology and systems genetics [1]. It is a tool for systems genetics and predictive medicine, which aims to predict and potentially avoid phenotypic outcomes such as diseases [2]. The platform supports the integration of networks of genes, transcripts, and traits, which is crucial for understanding complex genetic interactions and their implications for personalized medicine [10]. Additionally, GeneNetwork.org facilitates the comparison of data on drug responses with gene expression patterns, which is essential for tailoring therapeutic strategies to individual genetic profiles [9].",
+    "The information on GeneNetwork.org aids in developing new treatments for diseases in several ways:  1. **Insight into Gene Function**: GeneNetwork.org provides insights into gene function and how altered gene function can lead to disease. This understanding is crucial for translating genetic discoveries into new therapeutics, as it helps elucidate the mechanisms of action for newly identified disease genes, which is a major bottleneck in drug development [1].  2. **Predictive Medicine and Systems Genetics**: The platform is an exciting resource for predictive medicine and systems genetics. It integrates data from multiple species and omics analyses, which can be used to predict phenotypic outcomes such as disease, potentially allowing for the development of treatments that can prevent these outcomes [2], [4].  3. **Identification of Drug Targets**: Genetic information from GeneNetwork.org can be used to identify new targets for pharmaceutical intervention. This includes providing information about the long-term safety of pathway interventions, which is crucial for developing effective and safe treatments [5].  4. **Exploratory and Statistical Analysis**: GeneNetwork.org is designed for exploratory and statistical analysis of large phenotype and genome datasets. This makes it practical to compare data on drug responses with gene expression patterns, facilitating the identification of potential therapeutic targets [8].  5. **Studying Gene Networks**: By studying networks of genes, proteins, metabolites, and other biomarkers, GeneNetwork.org helps uncover disease genes. This network-based approach combines the effects of multiple genes, producing stronger signals and reducing the complexity of statistical analyses, which can accelerate the discovery of new treatments [10].  Overall, GeneNetwork.org serves as a comprehensive tool for researchers to explore genetic data and develop insights that are critical for the creation of new therapeutic strategies.",
+    "A gene network is a graphical model comprised of nodes and edges, where the nodes typically represent genes, gene products, or other biological entities [1]. These networks illustrate how genes do not function in isolation but operate in complex networks that define the behavior of biological systems [2]. Understanding gene networks is crucial for interpreting the roles of individual genes within the broader context of these networks, which can provide insights into complex system behaviors, including diseases [1], [2]. By considering genes within their networks, researchers can better understand the interrelationships and regulatory mechanisms that contribute to phenotypic traits and disease processes [4].",
+    "Researchers identify important genes for certain traits using GeneNetwork.org through a series of steps and tools provided by the platform:  1. **Data Selection and Trait Mining**: Researchers begin by selecting a data set and mining it for traits of interest based on user search queries [1]. This involves using the main search page to query specific data sets and identify traits that are relevant to their study.  2. **Trait Collection and Analysis**: Once traits are identified, they are selected and placed in a collection for further inspection and quantitative analysis [1]. This allows researchers to organize and focus on specific traits for deeper investigation.  3. **Advanced Search Options**: GeneNetwork offers advanced search options that enable researchers to query data sets for specific genomic intervals and locate traits with the highest likelihood ratio statistic (LRS) values, which are indicative of strong genetic associations [4].  4. **Correlation and Genetic Linkage Mapping**: Researchers can establish associations between transcript abundance, phenotypic traits, and genotype using correlation or genetic linkage mapping functions [5]. This helps in identifying candidate genes linked to specific traits.  5. **QTL Analysis and Network Graphs**: The platform allows for the generation of quantitative trait loci (QTL) analyses, network graphs, and correlation matrices, which are essential for understanding the genetic architecture of complex traits [3].  By utilizing these tools and processes, researchers can effectively identify and analyze genes that are important for specific traits using GeneNetwork.org.",
+    "GeneNetwork.org can assist in understanding complex traits like height or intelligence through several key features:  1. **Analytical Tools and Data Sets**: GeneNetwork provides a variety of analytical tools that allow users to compare traits with numerous datasets available from other researchers. This includes microarray data of gene expression in the brain and other phenotypic data, which can be crucial for studying complex traits [1].  2. **Systems Genetics Approach**: The platform offers a systems genetics approach, which helps illuminate the relationships between different biological system levels, such as the genome, transcriptome, and phenome. This comprehensive view can provide insights into the roles of individual genes and developmental pathways involved in complex traits [2].  3. **Correlation and Genetic Linkage Mapping**: GeneNetwork allows for the establishment of associations between transcript abundance, phenotypic traits, and genotype using correlation or genetic linkage mapping functions. This can help identify genetic factors contributing to complex traits like height or intelligence [6].  4. **Data Mining and Trait Correlations**: The platform can be used to study correlations between traits and perform data mining in genomic regions containing candidates for quantitative trait genes. This feature is particularly useful for identifying genetic components of complex traits [4].  5. **Multi-Omics Analysis**: GeneNetwork has been updated to include multi-omics analysis, which integrates various types of biological data. This holistic approach can enhance the understanding of complex traits by considering multiple layers of biological information [7].  Overall, GeneNetwork.org provides a comprehensive suite of tools and data that can facilitate the exploration and understanding of complex traits like height and intelligence through a systems genetics framework.",
+    "Yes, there are known genetic mutations that cause premature aging. Some specific genetic syndromes associated with premature aging include:  1. Hutchinson-Gilford Progeria Syndrome, which is caused by mutations in the LMNA gene [4]. 2. Rothmund-Thomson syndrome and related disorders, which are associated with mutations in the RECQL4 gene [4]. 3. Ataxia-telangiectasia, which is another genetic disorder linked to premature aging [4].  Additionally, Martin (1978) listed 162 genetic syndromes in humans that exhibit some or many signs of premature aging [1]. These conditions highlight the connection between genetic mutations and premature aging.",
+    "The research done through GeneNetwork.org has several practical applications:  1. **Predictive Medicine and Systems Genetics**: GeneNetwork is a valuable resource for predictive medicine and systems genetics, providing tools and data for multi-omics analysis across multiple species [1].  2. **Teaching Tool**: It serves as a teaching tool in neuroscience and genetics, allowing educators to use it for dry-lab teaching and helping students explore gene-to-phenotype relationships [2].  3. **Exploration of Systems Genetics Data**: GeneNetwork is used to explore systems genetics data, which is crucial for defining biological networks and predicting molecular interactions [4].  4. **Complex Systems Biology Approaches**: It provides datasets and tools for complex systems biology approaches, aiding in the generation or prediction of higher-order gene functions [5].  5. **Virtual Laboratory for Hypothesis Testing**: GeneNetwork can be used as a virtual laboratory to test specific biological hypotheses or to generate new ideas from scratch [8].  6. **Identification of Regulatory Genes**: The platform can identify novel potential master regulatory genes for further investigation, enhancing the understanding of genetic regulation [9].  7. **User-Friendly Systems Genetics Analyses**: It allows researchers without advanced bioinformatics skills to perform systems genetics analyses, making it accessible to a broader range of scientists [10].",
+    "To access and use the data available on GeneNetwork.org, you can follow these steps:  1. **Navigating to the Website**: Start by visiting the GeneNetwork website at www.genenetwork.org [8].  2. **Searching for Data**: There are two primary ways to search for data on GeneNetwork:    - Use the global search bar located at the top of the page. This feature allows you to search for genes, mRNAs, or proteins across all datasets, providing data across various species, groups, and types of data [5].    - Alternatively, you can follow the main search workflow, which involves selecting a dataset, mining it for traits of interest based on user search queries, selecting traits from the search, and placing them in a collection for further inspection and quantitative analysis [3].  3. **Analyzing Data**: Once you have selected the data, GeneNetwork provides an analytical environment where you can perform correlation analysis and linkage mapping. This environment helps identify and substantiate gene targets for further research [7].  4. **Accessing Genotype Files**: If you need genotype files, they can be accessed directly via a specific URL: http://www.genenetwork.org/webqtl/main.py?FormID=sharinginfo&GN_AccessionId=600 [2].  5. **Using Additional Resources**: The banner menu on the main search page contains additional search options and helpful resources to assist with your analyses [3].  By following these steps, you can effectively access and utilize the data available on GeneNetwork.org for your research needs.",
+    "The provided context does not explicitly mention any specific recent discoveries made using GeneNetwork.org. However, it highlights the platform's capabilities and improvements, such as the addition of data from 10 species, multi-omics analysis, updated code, and new tools, which make it a valuable resource for predictive medicine and systems genetics [1]. Additionally, GeneNetwork.org is described as a powerful statistical platform for online network analyses and mapping, which could enable numerous breakthroughs in neuroscience and other fields [7]. While these improvements and capabilities suggest potential for discoveries, specific recent discoveries are not detailed in the context provided.",
+    "Scientists ensure the accuracy of the data on GeneNetwork.org through several methods:  1. **Quality Control and Normalization**: Data are entered into GeneNetwork after being processed through systems like PhenoGen, which have extensive capabilities for normalization and quality control [3].  2. **Quality Checking and Preprocessing**: Phenotypic data undergo quality checks and preprocessing before being uploaded to GeneNetwork. This includes normalization, removal of outliers, and transformation of data to achieve a normal distribution [8].  3. **Data Curation and Informatics Support**: The GeneNetwork.org team provides excellent data curation and informatics support to maintain data accuracy [4].  These steps help ensure that the data on GeneNetwork.org is accurate and reliable for scientific research.",
+    "The difference between looking at one gene and studying a whole gene network lies in the scope and context of the analysis. When examining a single gene, the focus is on understanding the role and function of that specific gene, often in isolation. This approach can be limited because it does not consider the interactions and relationships that gene may have with others.  In contrast, studying a whole gene network involves analyzing a system of interconnected genes, which provides a broader context. A gene network is a graphical model where nodes represent genes or gene products, and edges represent interactions between them [1]. This approach allows researchers to explore how multiple genes interact within biological pathways, potentially uncovering complex relationships and combined effects that a single-gene analysis might miss [2]. By studying gene networks, researchers can gain insights into the collective behavior of genes, which can be crucial for understanding complex diseases and biological functions [2]. Additionally, gene networks can help identify highly connected subgraphs that correspond to biologically relevant networks, aiding in the identification of causative genes and their regulatory roles [5]."
+  ],
+  "contexts": [
+    [
+      "GeneNetwork have reinvigorated it, including the addition  of data from  10 species, multi -omics  analysis, updated code, and new tools. The new GeneNetwork is now an exciting resource for  predictive medicine and systems genetics, which is constantly being maintained and improved.    Here, we give a brief overview of the process  for carrying out some of the most common  functions on GeneNetwork, as a gateway to deeper analyses , demonstrating how a small",
+      "of links to external resources for tracing the interrelationships of a gene among multiple Web-based resources. GeneNetwork also offers a number of correlation and mapping strategies for assessing associations among multiple genes and QTLs. GeneNetwork aims to make the study of complex traits through the use of systems genetics widely available to the scientific community. A powerful tool that can be integrated with GeneNetwork or used on",
+      "inbred strain; Reverse genetics; dbSNP; GeneWeaver; BioGPS; NCBI; GeneRIF; UCSC Genome  Browser; Gemma; GEO; Allen Brain Atlas; GWAS Catalog; GTEx; WebGestalt; PLINK;  Manhattan plot; eQTL analysis; R/qtl; WGCNA; Proteomics; Metabolomics; Metagenomics 1 Introduction GeneNetwork ( www.genenetwork.org , GN) is a web service for systems genetics. It started  in 2001 as WebQTL an online version of Ken Manlys Map Manager QT  program [ 1]",
+      "inbred strain; Reverse genetics; dbSNP; GeneWeaver; BioGPS; NCBI; GeneRIF; UCSC Genome  Browser; Gemma; GEO; Allen Brain Atlas; GWAS Catalog; GTEx; WebGestalt; PLINK;  Manhattan plot; eQTL analysis; R/qtl; WGCNA; Proteomics; Metabolomics; Metagenomics 1 Introduction GeneNetwork ( www.genenetwork.org , GN) is a web service for systems genetics. It started  in 2001 as WebQTL an online version of Ken Manlys Map Manager QT  program [ 1]",
+      "GeneNetwork http://www.genenetwork.org is anexample of a bioinformatics tool that can be used to explore systems genetics data. The importance of defining biological networks and predicting molecular interactions has been emphasized by several reports [1,2]. Such studies emphasize that when knowledge about DNA variation within popula- tions is interfaced with data on gene expression, protein interactions and DNA-protein binding, biological networks can be constructed that are predictive of the",
+      "GeneNetwork.org is also a valuable teaching tool. While mainly designed for researchers interested in testing gene-to- phenotype relationships, GeneNetwork. orghas been adapted for dry-lab teaching in neuroscience and genetics ( Grisham et al., 2017 ). A useful approach is to assign sets of vetted questions, such as the exam- ples discussed above, and to help students work toward answers, solutions, or novelquestions. Several examples relating to the",
+      "GeneNetwork.org is also a valuable teaching tool. While mainly designed for researchers interested in testing gene-to- phenotype relationships, GeneNetwork. orghas been adapted for dry-lab teaching in neuroscience and genetics ( Grisham et al., 2017 ). A useful approach is to assign sets of vetted questions, such as the exam- ples discussed above, and to help students work toward answers, solutions, or novelquestions. Several examples relating to the",
+      "subnetworks   GeneNetwork (www.genenetwork.org) is a depository of data- sets and tools for use in complex systems biology approaches in  order to generate or predict higher order gene function ( 23, 24 ).",
+      "GeneNetwork is an open-access database that collates genomic information of diverse experimental crosses and reference panels as well as phenotypic data from miscellaneous research groups [26]. Statistics Data generation, statistical analysis and graph creation were performed with SPSS Statistics 21 (IBM, Ehningen, Germany). As appropriate, mean and median values were further used for QTLanalysis. Phenotypic robustness for each strain was assessed by the",
+      "deposited in the GeneNetwork website (http://www.genenetwork.org) so that other investigators can look for correlations between gene expression patterns and phenotypic traits. The GeneNetwork is an open resource and consists of a set of linked resources for systems genetics. It has been designed for integration of networks of genes, transcripts, and traits such as toxicity, cancer susceptibility, and behavior for several species. Phenotypic QTLs using the"
+    ],
+    [
+      "GeneNetwork have reinvigorated it, including the addition  of data from  10 species, multi -omics  analysis, updated code, and new tools. The new GeneNetwork is now an exciting resource for  predictive medicine and systems genetics, which is constantly being maintained and improved.    Here, we give a brief overview of the process  for carrying out some of the most common  functions on GeneNetwork, as a gateway to deeper analyses , demonstrating how a small",
+      "users can take advantage of a systems genetics approach (Rosen et al., 2003, 2007). While the candidate gene approach asks which one gene mutation causes a particular disease, the systems genetics approach explores which phenotypes and diseases result from diverse sets of genetic and molecular markers (Rosen et al., 2003, 2007). The majority of data sets in GeneNetwork are collected from GRPs consisting of hundreds of diverse, inbred strains of",
+      "Based on this, Goh et al. created networks using data from the Online Mendelian Inheritance in Man (OMIM) [18]database that houses lists of disease gene links. Two networks emerged: the human disease network inwhich disease nodes were connected if they were caused by mutations in the same gene, and the disease gene network where gene nodes were",
+      "al., 2005). GeneNetwork is designed primarily as a web service for exploratory and statistical analysis of large published phenotype and genome datasets, and includes data from several species (see Supplementary Discussion). GeneNetwork includes extensive phenotype data extracted from the literature and submitted by users, which makes it practical to compare data on drug responses with gene expression patterns. Gene expression",
+      "GeneNetwork http://www.genenetwork.org is anexample of a bioinformatics tool that can be used to explore systems genetics data. The importance of defining biological networks and predicting molecular interactions has been emphasized by several reports [1,2]. Such studies emphasize that when knowledge about DNA variation within popula- tions is interfaced with data on gene expression, protein interactions and DNA-protein binding, biological networks can be constructed that are predictive of the",
+      "including correlation and network analysis to compare associations  between tissues and between other rodent or human data sets[32] Many of the Data Sets are amenable to systems genetics mapping and other methods and are accessible at GeneNetwork. The Description and Usage column provides details about the data set and potential",
+      "including correlation and network analysis to compare associations  between tissues and between other rodent or human data sets[32] Many of the Data Sets are amenable to systems genetics mapping and other methods and are accessible at GeneNetwork. The Description and Usage column provides details about the data set and potential",
+      "atic way. Users begin by selecting one or more human diseases and clicking on Compare. The genes associated with the selected disease are tested for enrichment against all sets of known associat ed genes for worm phenotypes. The result reveals functionally coherent , evolution- arily conserved gene networks. Alternatively, users can also start by selecting worm pheno types, which are tested against human diseases. In addition to cross -species",
+      "is tackling this immense challenge bystudying networks of genes, proteins,metabolites, and other biomarkers thatrepresent models of genuine biologicalpathways. Studying complex diseasesin terms of gene networks rather thanindividual genes or genomic loci shouldaid in uncovering disease genes. Withthis approach, the effects of multiplegenes in the network are combined,producing a stronger signal and reducingthe number of statistical tests of associ-ation that must be performed.",
+      "subnetworks   GeneNetwork (www.genenetwork.org) is a depository of data- sets and tools for use in complex systems biology approaches in  order to generate or predict higher order gene function ( 23, 24 )."
+    ],
+    [
+      "GeneNetwork http://www.genenetwork.org is anexample of a bioinformatics tool that can be used to explore systems genetics data. The importance of defining biological networks and predicting molecular interactions has been emphasized by several reports [1,2]. Such studies emphasize that when knowledge about DNA variation within popula- tions is interfaced with data on gene expression, protein interactions and DNA-protein binding, biological networks can be constructed that are predictive of the",
+      "Molecular Genetics and Genomics  1 3 as overexpression, knockdown, knockout and mutation  (Online Resource 1). Gene network construction Genegene interaction data were extracted from the STRING database (http://strin g-db.org/) (Christian etal. 2003), a web resource that includes comprehensively predicted and known interaction information. Then, the genegene interaction pairs were imported into Cytoscape software (Version 3.5.1) (http://cytos  cape.org/ ) (Smoot etal. 2011 ) to construct a",
+      "of links to external resources for tracing the interrelationships of a gene among multiple Web-based resources. GeneNetwork also offers a number of correlation and mapping strategies for assessing associations among multiple genes and QTLs. GeneNetwork aims to make the study of complex traits through the use of systems genetics widely available to the scientific community. A powerful tool that can be integrated with GeneNetwork or used on",
+      "GeneNetwork have reinvigorated it, including the addition  of data from  10 species, multi -omics  analysis, updated code, and new tools. The new GeneNetwork is now an exciting resource for  predictive medicine and systems genetics, which is constantly being maintained and improved.    Here, we give a brief overview of the process  for carrying out some of the most common  functions on GeneNetwork, as a gateway to deeper analyses , demonstrating how a small",
+      "is shown in Figure 1A. Associations between transcript abundance, phenotypic traits and genotype can be estab- lished either using correlation or genetic linkage mapping functions [29,30]. The main page of GeneNetwork at http://www.genenetwork.org  provides access to subsets of data through pull-down menus that allow specific data sets to be queried. The datasets can be further restricted using a single text box for specific database entries to query probe set or trait ID, or annotations associated with",
+      "genetics approaches can not only provide insights into the roles of  individual genes or developmental pathways but also illuminate  relationships between different levels of a biologic system, such as  the genome, transcriptome, and phenome [ 10]. One such resource  of systems genetics is the GeneNetwork website and resource  (www.genenetwork.org ) that provides access to a wide variety of  data such as genotypes (e.g., SNPs), phenotypes that are obtained",
+      "occurrence; GN, gene neighbor; GT, genetic interaction; LC, literature-curated protein interactions; MS, affinity purification/mass spectrome try; PG, phy- logenetic profiles; PI, fly protein interactions; TS, tertiary structure; and YH, yeast two-hybrid). Detailed descriptions are listed in Suppleme ntal Table S1. ( B) Essential genes were highly interconnected in HumanNet, and thus predictable from the network, as shown by ROC analysis. Genes were ranked by their sum",
+      "from co-regulation patterns found within tens of thousands of samples for which gene expression was measured. GeneNetwork provid es un- precedented resolution and predictive power across multip le cell types and tissues. Analogous to discovering patterns in expressi on data, the network of protein-protein interactions can also be comput ationally pre- dicted using various methods[381]. The combined current knowledge of how cells control functio ns",
+      "(http://string-db.org/ ). STRING creates networks representing the best available knowledge of gene interconnections. Each protein-protein interaction is annotated with scores indicating how likely an interaction should be true. Scores rank from 0 to 1, with one being the highest confidence. A score of 0.5 indicates roughly every second interaction might be erroneous. Gene-gene co-expression cor- relations were computed as Pearson product-moment correlations (r) in Genenetwork.org after removing outliers.",
+      "addition to this, GeneNetwork can be used to study correlations between traits and to perform data mining in genomic regions containing candidates for quantitative trait genes (Hoffman et al., 2011). All datasets in GeneNetwork are linked to a materials and methods information page that summarizes experimental details relating to the dataset. Databases within GeneNetwork include the transcriptome database, the BXD published"
+    ],
+    [
+      "users can take advantage of a systems genetics approach (Rosen et al., 2003, 2007). While the candidate gene approach asks which one gene mutation causes a particular disease, the systems genetics approach explores which phenotypes and diseases result from diverse sets of genetic and molecular markers (Rosen et al., 2003, 2007). The majority of data sets in GeneNetwork are collected from GRPs consisting of hundreds of diverse, inbred strains of",
+      "Based on this, Goh et al. created networks using data from the Online Mendelian Inheritance in Man (OMIM) [18]database that houses lists of disease gene links. Two networks emerged: the human disease network inwhich disease nodes were connected if they were caused by mutations in the same gene, and the disease gene network where gene nodes were",
+      "Genetics Home Reference - Genetics Home Reference provides consumer-friendly  information about the effects of genetic variations on human health.  http://ghr.nlm.nih.gov/   Gene Reviews  Features expert-authored, peer-reviewed, current disease descriptions  that apply genetic testing to the diagnosis, management, and genetic counseling of  patients and families with specific inherited conditions. www.genetests.org/servlet/access?",
+      "GeneNetwork http://www.genenetwork.org is anexample of a bioinformatics tool that can be used to explore systems genetics data. The importance of defining biological networks and predicting molecular interactions has been emphasized by several reports [1,2]. Such studies emphasize that when knowledge about DNA variation within popula- tions is interfaced with data on gene expression, protein interactions and DNA-protein binding, biological networks can be constructed that are predictive of the",
+      "of links to external resources for tracing the interrelationships of a gene among multiple Web-based resources. GeneNetwork also offers a number of correlation and mapping strategies for assessing associations among multiple genes and QTLs. GeneNetwork aims to make the study of complex traits through the use of systems genetics widely available to the scientific community. A powerful tool that can be integrated with GeneNetwork or used on",
+      "GeneNetwork have reinvigorated it, including the addition  of data from  10 species, multi -omics  analysis, updated code, and new tools. The new GeneNetwork is now an exciting resource for  predictive medicine and systems genetics, which is constantly being maintained and improved.    Here, we give a brief overview of the process  for carrying out some of the most common  functions on GeneNetwork, as a gateway to deeper analyses , demonstrating how a small",
+      "genetics approaches can not only provide insights into the roles of  individual genes or developmental pathways but also illuminate  relationships between different levels of a biologic system, such as  the genome, transcriptome, and phenome [ 10]. One such resource  of systems genetics is the GeneNetwork website and resource  (www.genenetwork.org ) that provides access to a wide variety of  data such as genotypes (e.g., SNPs), phenotypes that are obtained",
+      "eron Genetics Center ( https://www.regeneron.com/ge - netics-center ), and aims to identify rare loss-of-function  mutations in founder populations to delineate further the  genetic factors that underpin health and disease. This ini - tiative is also addressed at developing countries and those  in resource-limiting environments, under the coordina - tion of the Genomic Medicine Alliance ( http://www.ge - nomicmedicinealliance.org ), a founding partner of the",
+      "to understand the genetics of a variety of diseases andbiological systems including aging, the immune system and ironregulation [26,27,28,29,30]. Much of this work has been madeavailable through GeneNetwork (formerly WebQTL ) an on-line",
+      "GeneNetwork.org is also a valuable teaching tool. While mainly designed for researchers interested in testing gene-to- phenotype relationships, GeneNetwork. orghas been adapted for dry-lab teaching in neuroscience and genetics ( Grisham et al., 2017 ). A useful approach is to assign sets of vetted questions, such as the exam- ples discussed above, and to help students work toward answers, solutions, or novelquestions. Several examples relating to the"
+    ],
+    [
+      "Letters NATure GeNeTicsIn our testing dataset, 19.8% of participants were at   threefold  increased risk for at least 1 of the 5 diseases studied (Table 2). The potential to identify individuals at significantly higher genetic  risk, across a wide range of common diseases and at any age, poses a number of opportunities and challenges for clinical medicine. Where effective prevention or early detection strategies are  available, key issues will include the allocation of attention and",
+      "genetic risks of disease on risk-reducing health behaviour: Systematic  review with meta-analysis. BMJ. 2016;352:i1102. 57. Vernarelli JA. Impact of genetic risk assessment on nutrition-related life- style behaviours. Proc Nutr Soc . 2013;72(1):153159. 58. Marteau TM, French DP , Griffin SJ, et  al. Effects of communicating DNA- based disease risk estimates on risk-reducing behaviours. Cochrane  Database Syst Rev . 2010;(10).  59. National Human Genome Research Institute. All about The Human",
+      "personalized screening based on age and  polygenic risk profile. 12 Pashayan N, Pharoah P. Translating genomics  into improved population screening: hype or  hope? Hum. Genet.  130(1), 1921 (2011). 13 Pharoah PD, Antoniou A, Bobrow M,  Zimmern RL, Easton DF, Ponder BA. Polygenic susceptibility to breast cancer and  implications for prevention. Nat. Genet.  31(1),  3336 (2002). nn\t Examines the potential for prediction of  risk based on common genetic variation and  compares this with the prediction that",
+      "Eur J Hum Genet. 12. Janssens AC, van Duijn CM (2008) Genome-based prediction of common diseases: advances and prospects. Hum Mol Genet 17: R166173. 13. Wray NR, Goddard ME, Visscher PM (2007) Prediction of individual genetic risk to disease from genome-wide association studies. Genome Res 17:15201528. 14. Wray NR, Goddard ME, Visscher PM (2008) Prediction of individual genetic risk of complex disease. Curr Opin Genet Dev 18: 257263. 15. Jakobsdottir J, Gorin MB, Conley YP, Ferrell RE, Weeks DE (2009)",
+      "within the general population and toutedfor its potential contribution to personal-ized medicine (1315), although the un-derlying clinical utility has yet to bedemonstrated (16,17). Given the poten-tial for individual genetic risk to beempirically quantied and rapidly com-municated, it is of interest to both clini-cians and the general public to discover ifmodiable characteristics like diet canmitigate risk in individuals empiricallydened as high risk on the basis ofgenotype.",
+      "Comprehension of Genomic Risk for  Diabetes  Public Health Genomics 2014;17:95104  DOI: 10.1159/000358413103  9 Green MJ, Peterson SK, Baker MW, Harper  GR, Friedman LC, Rubinstein WS, Mauger DT: Effect of a computer-based decision aid on knowledge, perceptions, and intentions about genetic testing for breast cancer suscep-tibility: a randomized controlled trial. JAMA 2004;    292:   442452.   10 Bernhardt JM, McClain J, Parrott RL: Online",
+      "Comparison of family history and SNPs for predicting risk of complex disease. PLoS Ge-net 2012;    8:e1002973.    Downloaded from http://karger.com/phg/article-pdf/17/2/95/3426597/000358413.pdf by guest on 03 July 2023",
+      "Genetics Home Reference - Genetics Home Reference provides consumer-friendly  information about the effects of genetic variations on human health.  http://ghr.nlm.nih.gov/   Gene Reviews  Features expert-authored, peer-reviewed, current disease descriptions  that apply genetic testing to the diagnosis, management, and genetic counseling of  patients and families with specific inherited conditions. www.genetests.org/servlet/access?",
+      "Khoury, M. J. (2006). Family history of type 2 diabetes: apopulation-based screening tool for prevention? Genetics in Medicine, 8 (2), 102 108. Hunter, D. J., Khoury, M. J., & Drazen, J. M. (2008). Letting the genome out of the bottle will we get our wish? The New England Journal of Medicine, 358 (2), 105 107. Ioannidis, J. P. A. (2009). Personalized genetic prediction: too limited, too expensive, or too soon? Annals of Internal Medicine, 150 (2), 139141.",
+      "genomic profiling for measuring susceptibility to common diseasesand targeting interventions. Genet Med 2004; 6:3847. 42Vineis P, Christiani DC. Genetic testing for sale. Epidemiology 2004; 15:35. 43Haga SB, Khoury MJ, Burke W. Genomic profiling to promote ahealthy lifestyle: not ready for prime time. Nat Genet 2003; 34:34750. 44Yang Q, Khoury MJ, Botto L et al. Improving the prediction of complex diseases by testing for multiple disease-susceptibility genes.Am J Hum Genet 2003; 72:63649."
+    ],
+    [
+      "GeneNetwork have reinvigorated it, including the addition  of data from  10 species, multi -omics  analysis, updated code, and new tools. The new GeneNetwork is now an exciting resource for  predictive medicine and systems genetics, which is constantly being maintained and improved.    Here, we give a brief overview of the process  for carrying out some of the most common  functions on GeneNetwork, as a gateway to deeper analyses , demonstrating how a small",
+      "GeneNetwork (www.genenetwork.org). The web -based software further allows extraction of sets of",
+      "al., 2005). GeneNetwork is designed primarily as a web service for exploratory and statistical analysis of large published phenotype and genome datasets, and includes data from several species (see Supplementary Discussion). GeneNetwork includes extensive phenotype data extracted from the literature and submitted by users, which makes it practical to compare data on drug responses with gene expression patterns. Gene expression",
+      "GeneNetwork is an open-access database that collates genomic information of diverse experimental crosses and reference panels as well as phenotypic data from miscellaneous research groups [26]. Statistics Data generation, statistical analysis and graph creation were performed with SPSS Statistics 21 (IBM, Ehningen, Germany). As appropriate, mean and median values were further used for QTLanalysis. Phenotypic robustness for each strain was assessed by the",
+      "GeneNetwork provides users with an array of analyticaltools to compare a given trait with a number of data setsavailable from other experimenters. Microarray data ofgene expression in the brain and data of other phenotypes are two such examples of possible tools. For this study, we",
+      "GeneNetwork http://www.genenetwork.org is anexample of a bioinformatics tool that can be used to explore systems genetics data. The importance of defining biological networks and predicting molecular interactions has been emphasized by several reports [1,2]. Such studies emphasize that when knowledge about DNA variation within popula- tions is interfaced with data on gene expression, protein interactions and DNA-protein binding, biological networks can be constructed that are predictive of the",
+      "distributed neuroscience data sharing with ever expanding prospects for future breakthroughs. GeneNetwork.org : genetic analysis for all neuroscientists Originally named webqtl, GeneNetwork.org is the oldest contin- uously operating website in biomedical research ( Williams, 1994). This massive database contains ;40 million datasets. GeneNetwork.org also offers a powerful statistical platform for online network analyses and mapping, enabling numerous mo-",
+      "distributed neuroscience data sharing with ever expanding prospects for future breakthroughs. GeneNetwork.org : genetic analysis for all neuroscientists Originally named webqtl, GeneNetwork.org is the oldest contin- uously operating website in biomedical research ( Williams, 1994). This massive database contains ;40 million datasets. GeneNetwork.org also offers a powerful statistical platform for online network analyses and mapping, enabling numerous mo-",
+      "addition to this, GeneNetwork can be used to study correlations between traits and to perform data mining in genomic regions containing candidates for quantitative trait genes (Hoffman et al., 2011). All datasets in GeneNetwork are linked to a materials and methods information page that summarizes experimental details relating to the dataset. Databases within GeneNetwork include the transcriptome database, the BXD published",
+      "abundance data sets directly within GeneNetwork's ana- lytical environment we provide simple web access to the data for the research community. In this environment, a combination of correlation analysis and linkage mapping provides the potential to identify and substantiate gene targets for saturation mapping and positional cloning. By integrating datasets from an unsequenced crop plant (bar- ley) in a database that has been designed for an animal model species (mouse) with well established genome"
+    ],
+    [
+      "This paper analyzes existing, publicly available data. These data sets accession numbers are provided in the Key Resource Table , and throughout the manuscript. Genotype les can be found at http://www.genenetwork.org/webqtl/main.py?FormID= sharinginfo&GN_AccessionId=600 . GeneNetwork.org original code is publicly available at https://github.com/genenetwork/genenetwork2 and https://github.com/ genenetwork/genenetwork1 .",
+      "GeneNetwork have reinvigorated it, including the addition  of data from  10 species, multi -omics  analysis, updated code, and new tools. The new GeneNetwork is now an exciting resource for  predictive medicine and systems genetics, which is constantly being maintained and improved.    Here, we give a brief overview of the process  for carrying out some of the most common  functions on GeneNetwork, as a gateway to deeper analyses , demonstrating how a small",
+      "GeneNetwork is an open-access database that collates genomic information of diverse experimental crosses and reference panels as well as phenotypic data from miscellaneous research groups [26]. Statistics Data generation, statistical analysis and graph creation were performed with SPSS Statistics 21 (IBM, Ehningen, Germany). As appropriate, mean and median values were further used for QTLanalysis. Phenotypic robustness for each strain was assessed by the",
+      "genetic variants (SNPs, insertions, deletions, duplications, etc.) that segregate in the family [ 13]. The strains are appropriate for systems genetics /systems biology analysis [ 14], genetic mapping and genetic correlations of parameter means, and thus constitute an ideal platform for toxicogenomic research [ 15]. All data are available at www.genenetwork.org. GeneNetwork exists in two forms, GN1 and GN2 [ 16]. GN2 is an expansion and renement of the features of GN1. A tutorial of how to use GN1 may be",
+      "al., 2005). GeneNetwork is designed primarily as a web service for exploratory and statistical analysis of large published phenotype and genome datasets, and includes data from several species (see Supplementary Discussion). GeneNetwork includes extensive phenotype data extracted from the literature and submitted by users, which makes it practical to compare data on drug responses with gene expression patterns. Gene expression",
+      "GeneNetwork (www.genenetwork.org). The web -based software further allows extraction of sets of",
+      "addition to this, GeneNetwork can be used to study correlations between traits and to perform data mining in genomic regions containing candidates for quantitative trait genes (Hoffman et al., 2011). All datasets in GeneNetwork are linked to a materials and methods information page that summarizes experimental details relating to the dataset. Databases within GeneNetwork include the transcriptome database, the BXD published",
+      "GeneNetwork provides users with an array of analyticaltools to compare a given trait with a number of data setsavailable from other experimenters. Microarray data ofgene expression in the brain and data of other phenotypes are two such examples of possible tools. For this study, we",
+      "deposited in the GeneNetwork website (http://www.genenetwork.org) so that other investigators can look for correlations between gene expression patterns and phenotypic traits. The GeneNetwork is an open resource and consists of a set of linked resources for systems genetics. It has been designed for integration of networks of genes, transcripts, and traits such as toxicity, cancer susceptibility, and behavior for several species. Phenotypic QTLs using the",
+      "genetics approaches can not only provide insights into the roles of  individual genes or developmental pathways but also illuminate  relationships between different levels of a biologic system, such as  the genome, transcriptome, and phenome [ 10]. One such resource  of systems genetics is the GeneNetwork website and resource  (www.genenetwork.org ) that provides access to a wide variety of  data such as genotypes (e.g., SNPs), phenotypes that are obtained"
+    ],
+    [
+      "GeneNetwork provides users with an array of analyticaltools to compare a given trait with a number of data setsavailable from other experimenters. Microarray data ofgene expression in the brain and data of other phenotypes are two such examples of possible tools. For this study, we",
+      "al., 2005). GeneNetwork is designed primarily as a web service for exploratory and statistical analysis of large published phenotype and genome datasets, and includes data from several species (see Supplementary Discussion). GeneNetwork includes extensive phenotype data extracted from the literature and submitted by users, which makes it practical to compare data on drug responses with gene expression patterns. Gene expression",
+      "data are entered into GeneNetwork after they have been shepherded through a system like PhenoGen that has extensive capabilities for normalization and quality control. A comparison of the brain gene expression datasets and some of the tools for data analysis available on PhenoGen and GeneNetwork is shown in Table 3, and more detailed information on features provided by each site is outlined in the Supplementary DiscussionHoffman et al. Page 5 Addict Biol . Author manuscript; available in PMC 2012 July 1.",
+      "(description of GeneNetwork provided by Dr. Robert W. Williams). Both of these websites focus to a large extent on correlations of behavioral phenotype with gene expression levels in recombinant inbred and inbred panels of mice and rats, and on QTL analyses, as a means to identify candidate genes for complex traits. What distinguishes PhenoGen, in addition to the tools for raw expression data analysis described above, is that the user can not only",
+      "including correlation and network analysis to compare associations  between tissues and between other rodent or human data sets[32] Many of the Data Sets are amenable to systems genetics mapping and other methods and are accessible at GeneNetwork. The Description and Usage column provides details about the data set and potential",
+      "including correlation and network analysis to compare associations  between tissues and between other rodent or human data sets[32] Many of the Data Sets are amenable to systems genetics mapping and other methods and are accessible at GeneNetwork. The Description and Usage column provides details about the data set and potential",
+      "by example in the Supplementary Methods, and in the Users Manual that can be downloaded from the website. There are a number of databases that investigators can use to assist in various aspects of gene expression data storage and mining (e.g., (Chesler et al., 2005; Galperin and Cochrane, 2009; Gentleman et al., 2004; Mailman et al., 2007; Saal et al., 2002; Swertz et al., 2010)). One relatively well-known database is GeneNetwork (www.genenetwork.org) (Chesler et",
+      "GeneNetwork have reinvigorated it, including the addition  of data from  10 species, multi -omics  analysis, updated code, and new tools. The new GeneNetwork is now an exciting resource for  predictive medicine and systems genetics, which is constantly being maintained and improved.    Here, we give a brief overview of the process  for carrying out some of the most common  functions on GeneNetwork, as a gateway to deeper analyses , demonstrating how a small",
+      "from co-regulation patterns found within tens of thousands of samples for which gene expression was measured. GeneNetwork provid es un- precedented resolution and predictive power across multip le cell types and tissues. Analogous to discovering patterns in expressi on data, the network of protein-protein interactions can also be comput ationally pre- dicted using various methods[381]. The combined current knowledge of how cells control functio ns",
+      "differentially expressed were further evaluated. Bioinformatic analyses were predominantly  performed using tools available at GeneNetwork. org, and included gene ontology, presence of cis- regulation or polymorphisms, phenotype correlations, and principal component analyses.  Comparisons of differential gene expression between groups showed little overlap. Gene Ontology  demonstrated distinct biological processes in each group with the combined exposure (RSE) being"
+    ],
+    [
+      "GeneNetwork.org is also a valuable teaching tool. While mainly designed for researchers interested in testing gene-to- phenotype relationships, GeneNetwork. orghas been adapted for dry-lab teaching in neuroscience and genetics ( Grisham et al., 2017 ). A useful approach is to assign sets of vetted questions, such as the exam- ples discussed above, and to help students work toward answers, solutions, or novelquestions. Several examples relating to the",
+      "GeneNetwork.org is also a valuable teaching tool. While mainly designed for researchers interested in testing gene-to- phenotype relationships, GeneNetwork. orghas been adapted for dry-lab teaching in neuroscience and genetics ( Grisham et al., 2017 ). A useful approach is to assign sets of vetted questions, such as the exam- ples discussed above, and to help students work toward answers, solutions, or novelquestions. Several examples relating to the",
+      "Category 1: Web Resources for Online Analysis of the Genetics of Alcoholism and More GeneNetwork  (www.genenetwork.org): This is a comprehensive resource for learning about genetics, but users may",
+      "GeneNetwork also features a phenotype database, a public repository of data from over 700 traits previously measured across several laboratories in BXD RI (and other) strains. These include behavioral, biochemical, and anatomical traits. The data consist of strain means, not raw data from individual mice, and so we use the term genetic correlation. Using this database, we performed correlation and network analyses to identify relationships with",
+      "biological function of the new gene list. As mentioned previously, GeneNetwork (www.genenetwork.org) is a collaborative Web-based resource equipped with tools and features for studying gene/gene and exploring genetic correlates to neurobehavioral phenotypes (Chesler et al., 2003, 2004). The Web site is home to a growing collection of gene expression and phenotypic data from a variety of species and brain regions, with a host",
+      "(description of GeneNetwork provided by Dr. Robert W. Williams). Both of these websites focus to a large extent on correlations of behavioral phenotype with gene expression levels in recombinant inbred and inbred panels of mice and rats, and on QTL analyses, as a means to identify candidate genes for complex traits. What distinguishes PhenoGen, in addition to the tools for raw expression data analysis described above, is that the user can not only",
+      "with another database, GeneNetwork, correlating behavioral phenotypes with geneO'Brien et al. Page 11 Int Rev Neurobiol . Author manuscript; available in PMC 2014 July 21. NIH-PA Author Manuscript NIH-PA Author Manuscript NIH-PA Author Manuscript",
+      "interested in behavioral variation and in ways to exploit bioinformatic resources and  methods to dissect and (we hope) reassemble and model behavior. You do not need to be a  statistician or geneticist to use these tools. In order to use GeneNetwork, we have to start with some ground rules and assumptions. The  first is that behavioral traits must vary significantly. This is a chapter about behavioral  variation  with an equal emphasis on both words. If a behavior is a \"fixed action pattern\" that",
+      "facilitated through the development of GeneNetwork(www.genenetwork.org), an Inte rnet resource for the multi- variate genetic analysis of complex traits in genetic reference populations (Chesler et al. 2003, 2004; Wang et al. 2003). GeneNetwork aids in identication of candidate genesand bio-molecular mechanisms underlying addiction-relatedphenotypes and includes a wealth of data on mRNAexpression proles from various tissues of the centralnervous system (Chesler et al. 2005; Peirce et al. 2006;",
+      "deposited in the GeneNetwork website (http://www.genenetwork.org) so that other investigators can look for correlations between gene expression patterns and phenotypic traits. The GeneNetwork is an open resource and consists of a set of linked resources for systems genetics. It has been designed for integration of networks of genes, transcripts, and traits such as toxicity, cancer susceptibility, and behavior for several species. Phenotypic QTLs using the"
+    ],
+    [
+      "of importance in the emergence of precision medicine ( Curtis, 2015 ; Desautels et al., 2014 ;  Glade Bender et al., 2015 ; Jorgensen, 2015 ; Kummar et al., 2015 ; Marquet et al., 2015 ;  Rubin, 2014 ) wherein therapeutic strategies need to be aligned with specific properties of  tumors. Methods GeneNetwork and WebGestalt GeneNetwork is an open access, online data analysis resource for systems biology and  systems genetics. It contains a large number of microarray datasets from multiple tissues of",
+      "gathered together into an easily accessible format, not siloed into disparate data pools that  cannot easily be integrated, valid ated, o r extended.  This approach will allow us to make animal  models of so called  precision medicine, although perhaps more accurately, we want   predictive medicine , where a phenotypic outcome (such as disease) can be predicted , and  avoided .    GeneNetwork   (genenetwork.or g; GN) is  one tool for systems genetics and predictive medicine,",
+      "The GeneNetwork site is supported by the University of Tennessee Center for Integrative and  Translational Genomics, NI GMS Systems Genetics and Precision Medicine Project (R01  GM123489, 2017 -2021), NIDA Core Center of Excellence in Transcriptomics, Systems Genetics,  and the Addictome (P30 DA044223, 2017 -2022), NIA Translational Systems Genetics of  Mitochondria, Metabolism,  and Aging (R01AG043930, 2013 -2018), NIAAA Integrative",
+      "The GeneNetwork site is supported by the University of Tennessee Center for Integrative and  Translational Genomics, NI GMS Systems Genetics and Precision Medicine Project (R01  GM123489, 2017 -2021), NIDA Core Center of Excellence in Transcriptomics, Systems Genetics,  and the Addictome (P30 DA044223, 2017 -2022), NIA Translational Systems Genetics of  Mitochondria, Metabolism,  and Aging (R01AG043930, 2013 -2018), NIAAA Integrative",
+      "GeneNetwork have reinvigorated it, including the addition  of data from  10 species, multi -omics  analysis, updated code, and new tools. The new GeneNetwork is now an exciting resource for  predictive medicine and systems genetics, which is constantly being maintained and improved.    Here, we give a brief overview of the process  for carrying out some of the most common  functions on GeneNetwork, as a gateway to deeper analyses , demonstrating how a small",
+      "eron Genetics Center ( https://www.regeneron.com/ge - netics-center ), and aims to identify rare loss-of-function  mutations in founder populations to delineate further the  genetic factors that underpin health and disease. This ini - tiative is also addressed at developing countries and those  in resource-limiting environments, under the coordina - tion of the Genomic Medicine Alliance ( http://www.ge - nomicmedicinealliance.org ), a founding partner of the",
+      "distributed neuroscience data sharing with ever expanding prospects for future breakthroughs. GeneNetwork.org : genetic analysis for all neuroscientists Originally named webqtl, GeneNetwork.org is the oldest contin- uously operating website in biomedical research ( Williams, 1994). This massive database contains ;40 million datasets. GeneNetwork.org also offers a powerful statistical platform for online network analyses and mapping, enabling numerous mo-",
+      "distributed neuroscience data sharing with ever expanding prospects for future breakthroughs. GeneNetwork.org : genetic analysis for all neuroscientists Originally named webqtl, GeneNetwork.org is the oldest contin- uously operating website in biomedical research ( Williams, 1994). This massive database contains ;40 million datasets. GeneNetwork.org also offers a powerful statistical platform for online network analyses and mapping, enabling numerous mo-",
+      "al., 2005). GeneNetwork is designed primarily as a web service for exploratory and statistical analysis of large published phenotype and genome datasets, and includes data from several species (see Supplementary Discussion). GeneNetwork includes extensive phenotype data extracted from the literature and submitted by users, which makes it practical to compare data on drug responses with gene expression patterns. Gene expression",
+      "deposited in the GeneNetwork website (http://www.genenetwork.org) so that other investigators can look for correlations between gene expression patterns and phenotypic traits. The GeneNetwork is an open resource and consists of a set of linked resources for systems genetics. It has been designed for integration of networks of genes, transcripts, and traits such as toxicity, cancer susceptibility, and behavior for several species. Phenotypic QTLs using the"
+    ],
+    [
+      "mation on gene function and how altered function leads to disease. Elucidating the mechanisms of action for newly minted disease genes is amajor bottleneck in translating genetic discoveries into new therapeutics.Addressing this limitation, it has been shown that networks can provideinsight on gene function [71,72] . The premise behind this is simple dgenes",
+      "GeneNetwork have reinvigorated it, including the addition  of data from  10 species, multi -omics  analysis, updated code, and new tools. The new GeneNetwork is now an exciting resource for  predictive medicine and systems genetics, which is constantly being maintained and improved.    Here, we give a brief overview of the process  for carrying out some of the most common  functions on GeneNetwork, as a gateway to deeper analyses , demonstrating how a small",
+      "of importance in the emergence of precision medicine ( Curtis, 2015 ; Desautels et al., 2014 ;  Glade Bender et al., 2015 ; Jorgensen, 2015 ; Kummar et al., 2015 ; Marquet et al., 2015 ;  Rubin, 2014 ) wherein therapeutic strategies need to be aligned with specific properties of  tumors. Methods GeneNetwork and WebGestalt GeneNetwork is an open access, online data analysis resource for systems biology and  systems genetics. It contains a large number of microarray datasets from multiple tissues of",
+      "gathered together into an easily accessible format, not siloed into disparate data pools that  cannot easily be integrated, valid ated, o r extended.  This approach will allow us to make animal  models of so called  precision medicine, although perhaps more accurately, we want   predictive medicine , where a phenotypic outcome (such as disease) can be predicted , and  avoided .    GeneNetwork   (genenetwork.or g; GN) is  one tool for systems genetics and predictive medicine,",
+      "vidual patients. For the time being, the contribu - tion of genetic information to therapy is most likely to come through the drug-discovery pipe - line. Information from genetic studies could be used to identify new targets for pharmaceutical intervention that have validated effects on physi - ological characteristics, to provide information about new and existing targets (e.g., clues about the long-term safety of pathway intervention), 32",
+      "GeneNetwork.org is also a valuable teaching tool. While mainly designed for researchers interested in testing gene-to- phenotype relationships, GeneNetwork. orghas been adapted for dry-lab teaching in neuroscience and genetics ( Grisham et al., 2017 ). A useful approach is to assign sets of vetted questions, such as the exam- ples discussed above, and to help students work toward answers, solutions, or novelquestions. Several examples relating to the",
+      "GeneNetwork.org is also a valuable teaching tool. While mainly designed for researchers interested in testing gene-to- phenotype relationships, GeneNetwork. orghas been adapted for dry-lab teaching in neuroscience and genetics ( Grisham et al., 2017 ). A useful approach is to assign sets of vetted questions, such as the exam- ples discussed above, and to help students work toward answers, solutions, or novelquestions. Several examples relating to the",
+      "al., 2005). GeneNetwork is designed primarily as a web service for exploratory and statistical analysis of large published phenotype and genome datasets, and includes data from several species (see Supplementary Discussion). GeneNetwork includes extensive phenotype data extracted from the literature and submitted by users, which makes it practical to compare data on drug responses with gene expression patterns. Gene expression",
+      "biological function of the new gene list. As mentioned previously, GeneNetwork (www.genenetwork.org) is a collaborative Web-based resource equipped with tools and features for studying gene/gene and exploring genetic correlates to neurobehavioral phenotypes (Chesler et al., 2003, 2004). The Web site is home to a growing collection of gene expression and phenotypic data from a variety of species and brain regions, with a host",
+      "is tackling this immense challenge bystudying networks of genes, proteins,metabolites, and other biomarkers thatrepresent models of genuine biologicalpathways. Studying complex diseasesin terms of gene networks rather thanindividual genes or genomic loci shouldaid in uncovering disease genes. Withthis approach, the effects of multiplegenes in the network are combined,producing a stronger signal and reducingthe number of statistical tests of associ-ation that must be performed."
+    ],
+    [
+      "considering single genes in the context of a whole gene network may provide thenecessary context within which to interpr et the disease role a given gene may play. Constructing gene networks can provide a convenient framework for exploring the context within which single genes operate. A network is simply a graphicalmodel comprised of nodes and edges. For gene networks associated with biological systems, the nodes in the network typically represent genes, gene products, or other",
+      "Genes do not carry out their functions in isolation of other genes, but instead oper- ate in complex networks that together, in a context-specic way, dene the complex behavior that emerges from biological systems. Therefore, understanding gene net- works in a diversity of contexts will lead to an increased understanding of complex system behavior, including disease. The reductionist approach to elucidating the complexity of biological systems",
+      "of links to external resources for tracing the interrelationships of a gene among multiple Web-based resources. GeneNetwork also offers a number of correlation and mapping strategies for assessing associations among multiple genes and QTLs. GeneNetwork aims to make the study of complex traits through the use of systems genetics widely available to the scientific community. A powerful tool that can be integrated with GeneNetwork or used on",
+      "genotypes and phenotypes, geneticists hope to discover and interpret the network of causal genotype-phenotype relationships that determine a trait of interest. Systems genetics research often follows a workow of nding a gene network, nding regulators of that network, and then performing a focused ge ne perturbation experiment to determine the role of the associated network on gene expre ssion or function. To be- gin, a large gene correlation graph must be sifted through , to nd a highly connected",
+      "genetics approaches can not only provide insights into the roles of  individual genes or developmental pathways but also illuminate  relationships between different levels of a biologic system, such as  the genome, transcriptome, and phenome [ 10]. One such resource  of systems genetics is the GeneNetwork website and resource  (www.genenetwork.org ) that provides access to a wide variety of  data such as genotypes (e.g., SNPs), phenotypes that are obtained",
+      "the risk of missing important biological phenomena [43].     8.4  Defining gene and QTL networks  In addition to the genetic dissection of phenotypic  variation using QTL mapping  techniques, systems geneticists are interested in r econstructing the biological net-  works that connect genes, proteins and other traits  based on their observed genetic  (co-)variation. In this context, biological network s are often defined by graphical",
+      "GeneNetwork http://www.genenetwork.org is anexample of a bioinformatics tool that can be used to explore systems genetics data. The importance of defining biological networks and predicting molecular interactions has been emphasized by several reports [1,2]. Such studies emphasize that when knowledge about DNA variation within popula- tions is interfaced with data on gene expression, protein interactions and DNA-protein binding, biological networks can be constructed that are predictive of the",
+      "It is important to integrate the gene variants and environmental factors to the trait to understand the network controlling that trait.  In systems genetics approach, different trait networks are related to different networks of gene and environmental variants to find global genetic modulation of the complex phenotype. The availability of genetic reference panels makes it easy to acquire diverse phenotypic data and advanced computational models make it possible to analyse their relationship.   2.2.1.",
+      "GeneNetwork have reinvigorated it, including the addition  of data from  10 species, multi -omics  analysis, updated code, and new tools. The new GeneNetwork is now an exciting resource for  predictive medicine and systems genetics, which is constantly being maintained and improved.    Here, we give a brief overview of the process  for carrying out some of the most common  functions on GeneNetwork, as a gateway to deeper analyses , demonstrating how a small",
+      "genetic variants (SNPs, insertions, deletions, duplications, etc.) that segregate in the family [ 13]. The strains are appropriate for systems genetics /systems biology analysis [ 14], genetic mapping and genetic correlations of parameter means, and thus constitute an ideal platform for toxicogenomic research [ 15]. All data are available at www.genenetwork.org. GeneNetwork exists in two forms, GN1 and GN2 [ 16]. GN2 is an expansion and renement of the features of GN1. A tutorial of how to use GN1 may be"
+    ],
+    [
+      "Fig. 2.  GeneNetwork main search page and organization. Most analyses in GeneNetwork will  follow the steps shown in panels A  through D. In this workfl ow, a data set is selected ( A)  and mined for traits of interest based on user search queries ( B). Traits are then selected  from the search ( C) and placed in a collection for further inspection and quantitative analysis  (D). The banner menu contains additional search options and helpful resources under the",
+      "Fig. 2.  GeneNetwork main search page and organization. Most analyses in GeneNetwork will  follow the steps shown in panels A  through D. In this workfl ow, a data set is selected ( A)  and mined for traits of interest based on user search queries ( B). Traits are then selected  from the search ( C) and placed in a collection for further inspection and quantitative analysis  (D). The banner menu contains additional search options and helpful resources under the",
+      "Another powerful feature of GeneNetwork is the ability to create and analyze whole collections  of data. In Figure 3  there are boxes within the table that can be selected in order to form a trait  collection. To do this, select the boxes in the table that su it the interests of the study, and press  Add. This function allows groups of traits to be saved for later analysis such as the generation of  a QTL, a network graph, and correlation matrix, some of which will be investigated further in",
+      "analysis in GeneNetwork, but there is an even more direct way to answer the same question.  It is possible to query data sets in GeneNetwork from the Select and Search  page using  advanced options to locate the highest trait LRS values for any genomic interval, in this case  the region within 2 Mb of Comt . (Note: You can explore this and other search options  further by clicking the Advanced Search  button and reading the section Advanced",
+      "is shown in Figure 1A. Associations between transcript abundance, phenotypic traits and genotype can be estab- lished either using correlation or genetic linkage mapping functions [29,30]. The main page of GeneNetwork at http://www.genenetwork.org  provides access to subsets of data through pull-down menus that allow specific data sets to be queried. The datasets can be further restricted using a single text box for specific database entries to query probe set or trait ID, or annotations associated with",
+      "genetic mapping, and correlation of quantitative traits such as gene expression data and behavioral parameters (Wang  et al, 2003) . GeneNetwork employs  genotype data from 3809 markers, selected based on their being informative (i.e., different between progenitor strains). GeneNetwork outputs peak likelihood ratio statistic (LRS) locations for each trait, whic h can be directly converted to",
+      "GeneNetwork provides users with an array of analyticaltools to compare a given trait with a number of data setsavailable from other experimenters. Microarray data ofgene expression in the brain and data of other phenotypes are two such examples of possible tools. For this study, we",
+      "GeneNetwork have reinvigorated it, including the addition  of data from  10 species, multi -omics  analysis, updated code, and new tools. The new GeneNetwork is now an exciting resource for  predictive medicine and systems genetics, which is constantly being maintained and improved.    Here, we give a brief overview of the process  for carrying out some of the most common  functions on GeneNetwork, as a gateway to deeper analyses , demonstrating how a small",
+      "(description of GeneNetwork provided by Dr. Robert W. Williams). Both of these websites focus to a large extent on correlations of behavioral phenotype with gene expression levels in recombinant inbred and inbred panels of mice and rats, and on QTL analyses, as a means to identify candidate genes for complex traits. What distinguishes PhenoGen, in addition to the tools for raw expression data analysis described above, is that the user can not only",
+      "of links to external resources for tracing the interrelationships of a gene among multiple Web-based resources. GeneNetwork also offers a number of correlation and mapping strategies for assessing associations among multiple genes and QTLs. GeneNetwork aims to make the study of complex traits through the use of systems genetics widely available to the scientific community. A powerful tool that can be integrated with GeneNetwork or used on"
+    ],
+    [
+      "GeneNetwork provides users with an array of analyticaltools to compare a given trait with a number of data setsavailable from other experimenters. Microarray data ofgene expression in the brain and data of other phenotypes are two such examples of possible tools. For this study, we",
+      "genetics approaches can not only provide insights into the roles of  individual genes or developmental pathways but also illuminate  relationships between different levels of a biologic system, such as  the genome, transcriptome, and phenome [ 10]. One such resource  of systems genetics is the GeneNetwork website and resource  (www.genenetwork.org ) that provides access to a wide variety of  data such as genotypes (e.g., SNPs), phenotypes that are obtained",
+      "201 5Nature America, Inc.  All rights reserved. 6 ADVANCE ONLINE PUBLICATION  Nature Ge Neticsa n a ly s i s 11. Yang, J. et al. Common SNPs explain a large proportion of the heritability for human  height. Nat. Genet.  42, 565569 (2010). 12. Yang, J., Lee, S.H., Goddard, M.E. & Visscher, P.M. GCTA: a tool for genome-wide  complex trait analysis. Am. J. Hum. Genet.  88, 7682 (2011). 13. Lee, S.H., Yang, J., Goddard, M.E., Visscher, P.M. & Wray, N.R. Estimation of",
+      "addition to this, GeneNetwork can be used to study correlations between traits and to perform data mining in genomic regions containing candidates for quantitative trait genes (Hoffman et al., 2011). All datasets in GeneNetwork are linked to a materials and methods information page that summarizes experimental details relating to the dataset. Databases within GeneNetwork include the transcriptome database, the BXD published",
+      "medicine. GeneNetwork.org is a tool for quantitative genetics that started in 2001 as WebQTL [38]. It evolved from analyses of forward genetics in the BXD mouse family, to phenome-wide association studies and reverse genetics in a variety of species. Although GeneNetwork contains data for many species and populations, it most prominently contains data for the BXD family. Over 10,000 classical phenotypes, measured under a variety of environmental conditions, and",
+      "is shown in Figure 1A. Associations between transcript abundance, phenotypic traits and genotype can be estab- lished either using correlation or genetic linkage mapping functions [29,30]. The main page of GeneNetwork at http://www.genenetwork.org  provides access to subsets of data through pull-down menus that allow specific data sets to be queried. The datasets can be further restricted using a single text box for specific database entries to query probe set or trait ID, or annotations associated with",
+      "GeneNetwork have reinvigorated it, including the addition  of data from  10 species, multi -omics  analysis, updated code, and new tools. The new GeneNetwork is now an exciting resource for  predictive medicine and systems genetics, which is constantly being maintained and improved.    Here, we give a brief overview of the process  for carrying out some of the most common  functions on GeneNetwork, as a gateway to deeper analyses , demonstrating how a small",
+      "GeneNetwork http://www.genenetwork.org is anexample of a bioinformatics tool that can be used to explore systems genetics data. The importance of defining biological networks and predicting molecular interactions has been emphasized by several reports [1,2]. Such studies emphasize that when knowledge about DNA variation within popula- tions is interfaced with data on gene expression, protein interactions and DNA-protein binding, biological networks can be constructed that are predictive of the",
+      "GeneNetwork.org is also a valuable teaching tool. While mainly designed for researchers interested in testing gene-to- phenotype relationships, GeneNetwork. orghas been adapted for dry-lab teaching in neuroscience and genetics ( Grisham et al., 2017 ). A useful approach is to assign sets of vetted questions, such as the exam- ples discussed above, and to help students work toward answers, solutions, or novelquestions. Several examples relating to the",
+      "GeneNetwork.org is also a valuable teaching tool. While mainly designed for researchers interested in testing gene-to- phenotype relationships, GeneNetwork. orghas been adapted for dry-lab teaching in neuroscience and genetics ( Grisham et al., 2017 ). A useful approach is to assign sets of vetted questions, such as the exam- ples discussed above, and to help students work toward answers, solutions, or novelquestions. Several examples relating to the"
+    ],
+    [
+      "logical phenomena is often facilitated by the  study of genetic mutants, and, in the case of  humans, genetic disorders. Accordingly, a search  was made, over the years, for genetic disorders  characterized by premature aging. If DNA dam-  age and repair has anything to do with aging it  should be evidenced in such individuals. Martin  (1978) listed 162 genetic syndromes in humans with some or many signs of premature aging.  About 21 feahares are considered as markers for",
+      "[315] Szilard, L. On the nature of the aging process. Proc. Natl. Acad. Sci. USA 45:3545; 1959. [316] Vijg, J.; Dolle, M. E. Large genome rearrangements as a primary cause of aging. Mech. Ageing Dev. 123:907915; 2002. [317] Vijg, J. Somatic mutations and aging: a re-evaluation. Mutat. Res. 447:117135; 2000. [318] Martin, G. M. Genetic syndromes in Man with potential relevance to the pathobiology of aging. Birth Defects Orig. Artic. Ser. 14:539; 1978.",
+      "19  6. Milholland B, Suh Y , Vijg J.Mutation and catastrophe in the aging genome. Exp Gerontol.  2017;94:3440.  7. Maslov AY , Ganapathi S, Westerhof M, Quispe-Tintaya W, White RR, Van Houten B, etal.  DNA damage in normally and prematurely aged mice. Aging Cell. 2013;12:46777.  8. Blokzijl F, de Ligt J, Jager M, Sasselli V , Roerink S, Sasaki N, etal. Tissue-specific mutation  accumulation in human adult stem cells during life. Nature. 2016;538:2604.",
+      "143 Gonzalo S, Kreienkamp R & Askjaer P (2017) Hutchinson -Gilford Progeria  Syndrome: A premature aging disease caused by LMNA gene mutations.  Ageing Res. Rev.  33, 1829.  144 Lu L, Jin W & Wang LL (2017) Aging in Ro thmund -Thomson syndrome and  related RECQL4 genetic disorders. Ageing Res. Rev.  33, 3035.  145 de Renty C & Ellis NA (2017) Blooms syndrome: Why not premature aging?  Ageing Res. Rev.  33, 3651.  146 Shiloh Y & Lederman HM (2017) Ataxia -telangiectasia (A -T): An emerging",
+      "genetic disease model of premature aging, In: Harrison,D.E., eds, Genetic Effects on Aging II (Telford Press, Caldwell,NJ), pp. 521542. [2] Djawdan, M., Sugiyama, T., Schlaeger, L., Bradley, T.J. and Rose, M.R. (1996) Metabolic aspects of the trade-off between fecundity and longevity in Drosophila melanogaster ,Physiol. Zool. 69, 11751195. [3] Fleming, J.E., Spicer, G.S., Garrison, R.C. and Rose, M.R.",
+      "genes of a whole chromosome ineffective, couldbe a main causal factor in aging (Szilard, 1959).According to Maynard Smith, such types of mu-tations do not seem likely to be common enoughto be the main cause of aging. However, at thetime quantitative information on the possible age-related accumulation of different types of muta-tions in various tissues of mammals wascompletely lacking. The question, therefore,whether somatic mutations are a cause of aging,has not been resolved, more than four decadesafter",
+      "features of premature aging (16, 17). Subsequent experiments conrmed that mitochondrial DNA mutations and deletions were the driving force behind the observed accelerated aging phenotypes(18). THE LINK BETWEEN NUCLEAR GENOME INTEGRITY AND PREMATURE AGING The notion that the majority of currently identied progeria syndromes originate from defects in genome maintenance highlights the importance of the condition of DNA in the process of",
+      "Tryggvason K,ZhouZ.Genomicinstability inlaminopathy based premature aging,NatMed. 2005;11:780 785. 13.MisteliT,ScaffidiP.Genomeinstability inprogeria:when repairgetsold,NatMed. 2005;11:718 719. 14.PereiraS,Bourgeois P,NavarroC,EstevesVieiraV,CauP,De SandreGiovannoli A,LvyN.HGPSandrelatedpremature aging disorders: Fromgenomicidentification tothefirsttherapeutic  approaches, MechAgeingDev.2008;129:449 459. 15.SmithED,Kudlow BA,FrockRL,KennedyBK.Atypenuclear",
+      "Nature Genetics | Volume 55 | February 2023 | 268279 278 Article https://doi.org/10.1038/s41588-022-01279-621. Tiwari, V. & Wilson, D. M. 3rd. DNA damage and associated DNA  repair defects in disease and premature aging. Am. J. Hum. Genet.   105, 237257 (2019). 22. Tamae, D., Lim, P., Wuenschell, G. E. & Termini, J. Mutagenesis and repair induced by the DNA advanced glycation end product N2-1-(carboxyethyl)-2-deoxyguanosine in human cells. Biochemistry   50, 23212329 (2011).",
+      "[36] J.  de  Boer,  J.O.  Andressoo,  J.  de  Wit,  J.  Huijmans,  R.B.  Beems,  H.  van  Steeg,  et  al., Premature  aging  in  mice  decient  in  DNA  repair  and  transcription,  Science 296  (2002)  12761279. [37]  S.M.  Schuh-Huerta,  N.A.  Johnson,  M.P.  Rosen,  B.  Sternfeld,  M.I.  Cedars,  R.A. Reijo Pera,  Genetic  markers  of  ovarian  follicle  number  and  menopause  in women  of  multiple  ethnicities,  Hum.  Genet.  131  (2012)  17091724."
+    ],
+    [
+      "GeneNetwork have reinvigorated it, including the addition  of data from  10 species, multi -omics  analysis, updated code, and new tools. The new GeneNetwork is now an exciting resource for  predictive medicine and systems genetics, which is constantly being maintained and improved.    Here, we give a brief overview of the process  for carrying out some of the most common  functions on GeneNetwork, as a gateway to deeper analyses , demonstrating how a small",
+      "GeneNetwork.org is also a valuable teaching tool. While mainly designed for researchers interested in testing gene-to- phenotype relationships, GeneNetwork. orghas been adapted for dry-lab teaching in neuroscience and genetics ( Grisham et al., 2017 ). A useful approach is to assign sets of vetted questions, such as the exam- ples discussed above, and to help students work toward answers, solutions, or novelquestions. Several examples relating to the",
+      "GeneNetwork.org is also a valuable teaching tool. While mainly designed for researchers interested in testing gene-to- phenotype relationships, GeneNetwork. orghas been adapted for dry-lab teaching in neuroscience and genetics ( Grisham et al., 2017 ). A useful approach is to assign sets of vetted questions, such as the exam- ples discussed above, and to help students work toward answers, solutions, or novelquestions. Several examples relating to the",
+      "GeneNetwork http://www.genenetwork.org is anexample of a bioinformatics tool that can be used to explore systems genetics data. The importance of defining biological networks and predicting molecular interactions has been emphasized by several reports [1,2]. Such studies emphasize that when knowledge about DNA variation within popula- tions is interfaced with data on gene expression, protein interactions and DNA-protein binding, biological networks can be constructed that are predictive of the",
+      "subnetworks   GeneNetwork (www.genenetwork.org) is a depository of data- sets and tools for use in complex systems biology approaches in  order to generate or predict higher order gene function ( 23, 24 ).",
+      "GeneNetwork (www.genenetwork.org). The web -based software further allows extraction of sets of",
+      "resources, gene expression pro les, and gene network constructions, methods for the analysis of gene function have been revolutionised in the past few years. One great resource for the analysis of gene networks is the databaseGeneNetwork, which consists of a set of linked resources for systems genetics (Andreux et al., 2012). It has been designed for multiple scale integration of networks of genes,transcripts in multiple tissues. GeneNetwork is an interac-",
+      "files on GeneNetwork) will also reduce the energy barrier of adopting powerful systems  genetics and systems behavioral approaches. Web services such as GeneNetwork and its  companionsGeneWeaver ( Baker et al., 2012 ), WebGestalt ( Zhang et al., 2005 ), DAVID  (Huang et al., 2009a ; Huang et al., 2009b ), and the Allen Brain Atlas ( Lein et al., 2007 ) can now be used as virtual and free laboratories to test specific biological hypothesis, or they  can be used to generate new ideas ab initio .",
+      "Its use is centred upon user-specied genes and can identify novel potential master regulatory genes for further investigation. We are working to increase the functionality and power of the GeneNet- work and systems genetics further in a number of areas. In partic- ular, increasing the number of strains studied can increase the mapping resolution. By increasing the genetic diversity of the founders of an RI set, the potential for observing regulatory poly-",
+      "gration   enhances the chance to detect genuine modi  ers across  organs. GeneNetwork is a valuable platform that can be used by  researchers without advanced skills of bioinformatics to perform  systems  genetics   analyses. The next step would be to establish soft- ware tools that allow researchers to combine datasets from multiple  resources and mapping analyses in different crosses and species (e.g.  intercross, recombinant inbred lines, and human data).         References"
+    ],
+    [
+      "GeneNetwork have reinvigorated it, including the addition  of data from  10 species, multi -omics  analysis, updated code, and new tools. The new GeneNetwork is now an exciting resource for  predictive medicine and systems genetics, which is constantly being maintained and improved.    Here, we give a brief overview of the process  for carrying out some of the most common  functions on GeneNetwork, as a gateway to deeper analyses , demonstrating how a small",
+      "This paper analyzes existing, publicly available data. These data sets accession numbers are provided in the Key Resource Table , and throughout the manuscript. Genotype les can be found at http://www.genenetwork.org/webqtl/main.py?FormID= sharinginfo&GN_AccessionId=600 . GeneNetwork.org original code is publicly available at https://github.com/genenetwork/genenetwork2 and https://github.com/ genenetwork/genenetwork1 .",
+      "Fig. 2.  GeneNetwork main search page and organization. Most analyses in GeneNetwork will  follow the steps shown in panels A  through D. In this workfl ow, a data set is selected ( A)  and mined for traits of interest based on user search queries ( B). Traits are then selected  from the search ( C) and placed in a collection for further inspection and quantitative analysis  (D). The banner menu contains additional search options and helpful resources under the",
+      "Fig. 2.  GeneNetwork main search page and organization. Most analyses in GeneNetwork will  follow the steps shown in panels A  through D. In this workfl ow, a data set is selected ( A)  and mined for traits of interest based on user search queries ( B). Traits are then selected  from the search ( C) and placed in a collection for further inspection and quantitative analysis  (D). The banner menu contains additional search options and helpful resources under the",
+      "1. Data   Once you have navigated to genenetwork.org, t here are two ways to search for data in GN. The  first is to use the global search bar located at the top of the page  (Figure 1 ). This is a new  feature in GN that allows researchers to search for genes, mRNAs, or proteins across all of the  datasets. This will give the user data for that search term  across many different species, groups,  and types of data. Because of this, the global search bar is a good area to start ones searches if",
+      "data are entered into GeneNetwork after they have been shepherded through a system like PhenoGen that has extensive capabilities for normalization and quality control. A comparison of the brain gene expression datasets and some of the tools for data analysis available on PhenoGen and GeneNetwork is shown in Table 3, and more detailed information on features provided by each site is outlined in the Supplementary DiscussionHoffman et al. Page 5 Addict Biol . Author manuscript; available in PMC 2012 July 1.",
+      "abundance data sets directly within GeneNetwork's ana- lytical environment we provide simple web access to the data for the research community. In this environment, a combination of correlation analysis and linkage mapping provides the potential to identify and substantiate gene targets for saturation mapping and positional cloning. By integrating datasets from an unsequenced crop plant (bar- ley) in a database that has been designed for an animal model species (mouse) with well established genome",
+      "GeneNetwork (www.genenetwork.org). The web -based software further allows extraction of sets of",
+      "need to read the help files, FAQs, or one of the references(Chesler et al., 2003; Grisham et al., 2010, www.lifescied.org/content/9/2/98.full.pdf). GeneNetwork is one ofan interlinked trio of sites built up by NIAAA (GeneWeaverand WebGestalt are the other two) to house extensivedata for human, monkey, rat, mouse, and fruit fly. Itincludes hundreds of data sets on responsesto alcohol,particularly in a family of mice called the BXDs. Dataare linked with powerful gene analysis and mappingtools. Think of it as",
+      "al., 2005). GeneNetwork is designed primarily as a web service for exploratory and statistical analysis of large published phenotype and genome datasets, and includes data from several species (see Supplementary Discussion). GeneNetwork includes extensive phenotype data extracted from the literature and submitted by users, which makes it practical to compare data on drug responses with gene expression patterns. Gene expression"
+    ],
+    [
+      "GeneNetwork have reinvigorated it, including the addition  of data from  10 species, multi -omics  analysis, updated code, and new tools. The new GeneNetwork is now an exciting resource for  predictive medicine and systems genetics, which is constantly being maintained and improved.    Here, we give a brief overview of the process  for carrying out some of the most common  functions on GeneNetwork, as a gateway to deeper analyses , demonstrating how a small",
+      "18 GeneNetwork Time Machine : Full versions from 2009 to 2016 (mm9); UTHSC Genome  Browser Classic  and Newest ; UTHSC Galaxy  Servic e; UTHSC Bayesian Network  Web Server ; GeneNetwork Classic on Amazon Cloud ; GeneNetwork Classic Code on  GitHub ; GeneNetwork 2.0 Development Code on GitHub ; and GeneNetwork 2.0  Development.    Technologies or techniques:    None     Inventions, patent applications, and/or licenses:   None     Other products:   None",
+      "GeneNetwork http://www.genenetwork.org is anexample of a bioinformatics tool that can be used to explore systems genetics data. The importance of defining biological networks and predicting molecular interactions has been emphasized by several reports [1,2]. Such studies emphasize that when knowledge about DNA variation within popula- tions is interfaced with data on gene expression, protein interactions and DNA-protein binding, biological networks can be constructed that are predictive of the",
+      "addition to this, GeneNetwork can be used to study correlations between traits and to perform data mining in genomic regions containing candidates for quantitative trait genes (Hoffman et al., 2011). All datasets in GeneNetwork are linked to a materials and methods information page that summarizes experimental details relating to the dataset. Databases within GeneNetwork include the transcriptome database, the BXD published",
+      "GeneNetwork (www.genenetwork.org). The web -based software further allows extraction of sets of",
+      "subnetworks   GeneNetwork (www.genenetwork.org) is a depository of data- sets and tools for use in complex systems biology approaches in  order to generate or predict higher order gene function ( 23, 24 ).",
+      "distributed neuroscience data sharing with ever expanding prospects for future breakthroughs. GeneNetwork.org : genetic analysis for all neuroscientists Originally named webqtl, GeneNetwork.org is the oldest contin- uously operating website in biomedical research ( Williams, 1994). This massive database contains ;40 million datasets. GeneNetwork.org also offers a powerful statistical platform for online network analyses and mapping, enabling numerous mo-",
+      "distributed neuroscience data sharing with ever expanding prospects for future breakthroughs. GeneNetwork.org : genetic analysis for all neuroscientists Originally named webqtl, GeneNetwork.org is the oldest contin- uously operating website in biomedical research ( Williams, 1994). This massive database contains ;40 million datasets. GeneNetwork.org also offers a powerful statistical platform for online network analyses and mapping, enabling numerous mo-",
+      "1   GeneNetwork: a  continuously  updated tool for systems genetics analyses     Pamela M. Watson1, David G. Ashbrook1    1Department of Genetics, Genomics and Informatics, University of Tennessee Health Science  Center, Memphis, TN 38163, USA     Abstract     GeneNetwork and its earlier iteration , WebQTL, have now been an important database and  toolkit for quantitative trait genetics  research  for two decades. Recent improvements to",
+      "resources, gene expression pro les, and gene network constructions, methods for the analysis of gene function have been revolutionised in the past few years. One great resource for the analysis of gene networks is the databaseGeneNetwork, which consists of a set of linked resources for systems genetics (Andreux et al., 2012). It has been designed for multiple scale integration of networks of genes,transcripts in multiple tissues. GeneNetwork is an interac-"
+    ],
+    [
+      "GeneNetwork have reinvigorated it, including the addition  of data from  10 species, multi -omics  analysis, updated code, and new tools. The new GeneNetwork is now an exciting resource for  predictive medicine and systems genetics, which is constantly being maintained and improved.    Here, we give a brief overview of the process  for carrying out some of the most common  functions on GeneNetwork, as a gateway to deeper analyses , demonstrating how a small",
+      "files), and GeneNetwork (a free scientific web resource, http://www.genenetwork.org/). Statistical analysis was performed using GraphPad Prism (GraphPad Software, Inc., CA, USA).",
+      "data are entered into GeneNetwork after they have been shepherded through a system like PhenoGen that has extensive capabilities for normalization and quality control. A comparison of the brain gene expression datasets and some of the tools for data analysis available on PhenoGen and GeneNetwork is shown in Table 3, and more detailed information on features provided by each site is outlined in the Supplementary DiscussionHoffman et al. Page 5 Addict Biol . Author manuscript; available in PMC 2012 July 1.",
+      "thank the members of the GeneNetwork.org team for their assistance, excellent data curation, and informatics support. Conicts of Interest: The authors declare no conict of interest. References 1. Wilkinson, M.D.; Dumontier, M.; Aalbersberg, I.J.; Appleton, G.; Axton, M.; Baak, A.; Blomberg, N.; Boiten, J.W.; da Silva Santos, L.B.; Bourne, P .E.; et al. The FAIR Guiding Principles for scientic data management and stewardship. Sci. Data 2016 ,3, 160018. [CrossRef]",
+      "thank the members of the GeneNetwork.org team for their assistance, excellent data curation, and informatics support. Conicts of Interest: The authors declare no conict of interest. References 1. Wilkinson, M.D.; Dumontier, M.; Aalbersberg, I.J.; Appleton, G.; Axton, M.; Baak, A.; Blomberg, N.; Boiten, J.W.; da Silva Santos, L.B.; Bourne, P .E.; et al. The FAIR Guiding Principles for scientic data management and stewardship. Sci. Data 2016 ,3, 160018. [CrossRef]",
+      "thank the members of the GeneNetwork.org team for their assistance, excellent data curation, and informatics support. Conicts of Interest: The authors declare no conict of interest. References 1. Wilkinson, M.D.; Dumontier, M.; Aalbersberg, I.J.; Appleton, G.; Axton, M.; Baak, A.; Blomberg, N.; Boiten, J.W.; da Silva Santos, L.B.; Bourne, P .E.; et al. The FAIR Guiding Principles for scientic data management and stewardship. Sci. Data 2016 ,3, 160018. [CrossRef]",
+      "9 Scientific  Data  |           (2019) 6:258  | https://doi.org/10.1038/s41597-019-0171-x www.nature.com/scientificdata www.nature.com/scientificdata/with more than 10% missing information, low quality ( <5000), and redundant information were removed.  GeneNetwork genotypes, which were discrepant with our RNA-seq experiment, were tagged as unknown  (mean of 1% of the GeneNetwork genotypes/strain [0.05%   n  8%]). Finally, GeneNetwork and our RNA-seq",
+      "1.    Phenotypic data should be quality checked and preprocessed  before being uploaded to GeneNetwork. This includes nor- malization of data, removal of outliers or windsorization, even- tually transformation of data to obtain normal distribution.       2.    When uploading data to GeneNetwork for permanent and  public storage, make sure to follow the GeneNetwork naming  guide for phenotypes.       3.    When uploading your own data make sure that for any pheno-",
+      "1.    Phenotypic data should be quality checked and preprocessed  before being uploaded to GeneNetwork. This includes nor- malization of data, removal of outliers or windsorization, even- tually transformation of data to obtain normal distribution.       2.    When uploading data to GeneNetwork for permanent and  public storage, make sure to follow the GeneNetwork naming  guide for phenotypes.       3.    When uploading your own data make sure that for any pheno-",
+      "analysis of behavior and for neurologic diseases are provided in the study by Mulligan et al. (2017) . GeneNetwork.org is committed to data and code workflows that are FAIR compliant, ensuring that those who generate data and key ideas get the deserved credit. To further ensure effective and secure dissemination of data and ideas, as well as improved reproducibility, the GeneNetwork.org infrastructure is currently being redesigned using more modular structures and APIs that"
+    ],
+    [
+      "considering single genes in the context of a whole gene network may provide thenecessary context within which to interpr et the disease role a given gene may play. Constructing gene networks can provide a convenient framework for exploring the context within which single genes operate. A network is simply a graphicalmodel comprised of nodes and edges. For gene networks associated with biological systems, the nodes in the network typically represent genes, gene products, or other",
+      "is tackling this immense challenge bystudying networks of genes, proteins,metabolites, and other biomarkers thatrepresent models of genuine biologicalpathways. Studying complex diseasesin terms of gene networks rather thanindividual genes or genomic loci shouldaid in uncovering disease genes. Withthis approach, the effects of multiplegenes in the network are combined,producing a stronger signal and reducingthe number of statistical tests of associ-ation that must be performed.",
+      "traditional genetical genomics approaches. It should also be noted that our approach is different from studying gene-gene regulation within a pathway, which focuses on the interactive activities of individual gene pairs genes within a pathway. A biological pathway is defined as a series of molecular interactions and reactions. If there are subtle changes in the expression level of a few genes located in the upper cascade of a",
+      "genes rapidly that may be in the same genetic network as the gene you are interested in. Then you need to validate the role of that gene and to identify its function in that network. The point is this is a powerful methodology that can provide data in half an hour that allows you to form hypotheses that you can then spend years investigating. Reference Lee PD, Ge B, Greenwood CM et al 2006 Mapping cis-acting regulatory variation in recombi- nant congenic strains. Physiol Genomics 25:294302",
+      "ment to determine the role of the associated network ongene expression or function. To begin, a large genecorrelation graph must be sifted through, to find a highlyconnected subgraph that corresponds biologically to a genenetwork in which genes are expressed together, presumablyto regulate or subserve a common function. They must thenfind a small set of causative genes, highly correlated withthe subgraph and likely to regulate coexpression, to be usedas targets of focused investigation. By manipulating the",
+      "Confronted with this daunting complexity, the field often  progresses in small steps. A study may identify one or two relevant genes and assess their interactions with other factors. Gradually, genetic knowledge from many studies then can be assembled into a larger system of interactants that enables us to understand a set of related behaviors. We term this perspective behavioral genomics ( Fig. 2b ).2005 Nature Publishing Group  http://www.nature.com/natureneuroscience",
+      "Confronted with this daunting complexity, the field often  progresses in small steps. A study may identify one or two relevant genes and assess their interactions with other factors. Gradually, genetic knowledge from many studies then can be assembled into a larger system of interactants that enables us to understand a set of related behaviors. We term this perspective behavioral genomics ( Fig. 2b ).2005 Nature Publishing Group  http://www.nature.com/natureneuroscience",
+      "From the network, modules of coexpressed genes can be obtained, i.e. com-  munities of highly interconnected nodes within the graph. Such coexpressed  modules can then be studied as putative functional units, thereby considerably  reducing the dimensionality of the data. Different approaches have been proposed,  many of which are inspired by social network resear ch. Chesler et al. choose to  focus on sets of genes in which all nodes are inter connected; such sets are termed",
+      "large-scale human and experimental populations, focusing on how a single protein or RNA impacts disease will ultimately give way to how a network of gene interac- tions impacts disease. The integration of genetic, molecular proling, and clinical data has the potential to paint a more detailed picture of the particular network statesthat drive disease, and this in turn has the potential to lead to more progressive treat- ments of disease that may ultimately invol ve targeting of whole networks as opposed",
+      "from co-regulation patterns found within tens of thousands of samples for which gene expression was measured. GeneNetwork provid es un- precedented resolution and predictive power across multip le cell types and tissues. Analogous to discovering patterns in expressi on data, the network of protein-protein interactions can also be comput ationally pre- dicted using various methods[381]. The combined current knowledge of how cells control functio ns"
+    ]
+  ],
+  "task_id": [1,2,3,4,5,6,7,8,9,10,1,2,3,4,5,6,7,8,9,10]
+}
\ No newline at end of file