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+{
+  "titles": [
+    "2020 - Gene network a completely updated tool for systems genetics analyses.pdf",
+    "2012 - Using Genome-Wide Expression Profiling to Define Gene Networks Relevant to the Study of Complex Traits From RNA Integrity to Network Topology.pdf",
+    "2016 - A Systems-Level Understanding of Cardiovascular Disease through Networks.pdf",
+    "2011 - Using the PhenoGen Website for \u201cIn Silico\u201d Analysis of Morphine-Induced Analgesia Identifying Candidate Genes.pdf",
+    "2010 - Systems genetics analyses predict a transcription role for P2P-R Molecular confirmation that P2P-R is a transcriptional co-repressor.pdf",
+    "2020 - GeneNetwork a toolbox for systems genetics.pdf",
+    "2017 - GeneNetwork a toolbox for systems genetics.pdf",
+    "2009 - Detection and interpretation of expression quantitative trait loci (eQTL).pdf",
+    "2012 - Identifying Gene Networks Underlying the Neurobiology of Ethanol and Alcoholism.pdf",
+    "2011 - Peroxisomal L-bifunctional enzyme (Ehhadh) is essential for the production of medium-chain dicarboxylic acids.pdf"
+  ],
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+    "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 )."
+  ],
+  "answer": "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].",
+  "question": "How do researchers use GeneNetwork.org to study diseases?"
+}
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