{
"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?"
],
"answer": [
"Please try to rephrase your question to receive feedback",
"Please try to rephrase your question to receive feedback",
"GeneNetwork.org provides a platform for studying gene interactions and exploring genetic correlates to various phenotypes. It uses co-regulation patterns from tens of thousands of samples to construct networks that link DNA differences to traits. It also offers tools for assessing associations among multiple genes and QTLs. The platform can visualize the relative positions and numbers of possible interacting partners, their interaction type (positive or negative correlation), and in some cases, suggest the directionality of the interaction. It also allows users to study relationships between genes, pathways, and phenotypes in an easy-to-use format.",
"Please try to rephrase your question to receive feedback",
"Please try to rephrase your question to receive feedback"
],
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[
"GeneNetwork: A Toolbox for Systems GeneticsMegan K. Mulligan1, Khyobeni Mozhui2, Pjotr Prins1,2, Robert W. Williams11.Departmentof Genetics, Genomics, and Informatics, University of Tennessee Health ScienceCenter, Memphis, USA2.PreventiveMedicine, University of Tennessee Health Science Center, Memphis, USAAuthor ManuscriptAbstractThe goal of systems genetics is to understand the impact of genetic variation across all levels ofbiological organization, from mRNAs, proteins, and metabolites, to higher-order physiological andbehavioral traits.",
"Until highly accurate genomics networks can beconstructed from more complete data, inferences drawnfrom biological networks should be considered as hypothesis that need to be further tested with experimental method, where the results can then illuminatethe representation of the biological system. The predictive power of the genomics networks could be enhancedby more systematically integrating interactions of informational molecules, such as protein-protein interactions, protein-DNA interactions, protein-RNA interactions, RNA-RNA interactions, protein state information, methylation state, and interactions with metabolites, as these types of data have become available(Schadt et al. 2009).",
"GeneNetwork is an interactive software (Geisert et al. , 2009), which enables usersreadily to reconstruct genetic network based on microarraydata without being intimately involved in complicatedmathematical computation. Materials and methodsMiceOne pair of heterozygous (lew/ ) mice was purchasedfrom the Mouse Mutant Stock Resource colonies at TheJackson Laboratory (TJL). A breeding colony was thenestablished by mating them at the University of TennesseeHealth Science Center (UTHSC).",
"Until highly accurate genomics networks can beconstructed from more complete data, inferences drawnfrom biological networks should be considered as hypothesis that need to be further tested with experimental method, where the results can then illuminatethe representation of the biological system. The predictive power of the genomics networks could be enhancedby more systematically integrating interactions of informational molecules, such as protein-protein interactions, protein-DNA interactions, protein-RNA interactions, RNA-RNA interactions, protein state information, methylation state, and interactions with metabolites, as these types of data have become available(Schadt et al. 2009).",
"GeneNetwork can allow users to study relationships between genes, pathways, andphenotypes in an easy to use format. 28bioRxiv preprint doi: https://doi.org/10.1101/2020.12.23.424047; this version posted December 24, 2020. The copyright holder for this preprint(which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.",
"GeneNetwork: A Toolbox for Systems GeneticsMegan K. Mulligan1, Khyobeni Mozhui2, Pjotr Prins1,2, Robert W. Williams11.Departmentof Genetics, Genomics, and Informatics, University of Tennessee Health ScienceCenter, Memphis, USA2.PreventiveMedicine, University of Tennessee Health Science Center, Memphis, USAAuthor ManuscriptAbstractThe goal of systems genetics is to understand the impact of genetic variation across all levels ofbiological organization, from mRNAs, proteins, and metabolites, to higher-order physiological andbehavioral traits.",
"Those prior knowledge driven geneticsystem-level approaches do not necessarily overlap withgene network analyses which are used to find modulesof highly co-expressed genes with a gene of interest. Thegenerally held view is that genes which are associated orinteracting are more likely to share function and therebybuild up a network. However, this view seems to be theexception rather than the rule in gene networks (Gillisand Pavlidis 2012) since functional information withingene networks is typically concentrated in only a very fewinteractions whose properties cannot be reliably relatedto the rest of the network.",
"Peidis et al. BMC Systems Biology 2010, 4:14http://www.biomedcentral.com/1752-0509/4/14In 2005, we published the first report documentingthe ability of the systems genetics tool GeneNetwork topredict interactions between molecules that could bethen confirmed by molecular analysis [3]. The P2P-Rgene, coding for a hnRNP-related protein [4] that bindsboth the p53 [5] and Rb1 [4] tumor suppressor proteinswas used as a test molecule. P2P-R was entered intoGeneNetwork to search for a co-variant that was mosthighly co-expressed in three tissues of the BXD mousegenetic reference panel, ie,, cerebellum, hematopoieticstem cells and whole brain specimens.",
"GeneNetwork can allow users to study relationships between genes, pathways, andphenotypes in an easy to use format. 28bioRxiv preprint doi: https://doi.org/10.1101/2020.12.23.424047; this version posted December 24, 2020. The copyright holder for this preprint(which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.",
"Taking this approach a step further, GeneNetwork[99] is constructedfrom co-regulation patterns found within tens of thousands of samplesfor which gene expression was measured. GeneNetwork provides unprecedented resolution and predictive power across multiple cell typesand tissues. Analogous to discovering patterns in expression data, thenetwork of protein-protein interactions can also be computationally predicted using various methods[381]. The combined current knowledge of how cells control functionssuch as growth, movement, dierentiation, metabolism, communication, and response to stress or pathogens is captured in high-level pathway databases such as WikiPathways[188], Reactome[97] or KEGG[180].",
"GeneNetwork is an interactive software (Geisert et al. , 2009), which enables usersreadily to reconstruct genetic network based on microarraydata without being intimately involved in complicatedmathematical computation. Materials and methodsMiceOne pair of heterozygous (lew/ ) mice was purchasedfrom the Mouse Mutant Stock Resource colonies at TheJackson Laboratory (TJL). A breeding colony was thenestablished by mating them at the University of TennesseeHealth Science Center (UTHSC).",
"Network based methods of co-expression analysis haveproven useful in identifying evolutionarily conserved gene and protein interactions (Stuart,Segal, Koller, & Kim, 2003), revealing highly connected hub genes that are crucial forsurvival (Carter, Brechbuhler, Griffin, & Bond, 2004), and detecting cell-type specificnetworks, even amongst heterogeneous populations such as the nervous system (Oldham etal. , 2008).",
"Next to direct protein-protein interactions, geneticinteractions from model organisms, and interactions withinwww.frontiersin.orgNeuroinformatics of major neuropsychiatric disorderspathways can be valuable information for a functional relationbetween seemingly unrelated genes. Spatiotemporal analysis ofgene expression correlation in human brain (using BrainSpandevelopmental transcriptome data; Kang et al. , 2011) has identified three co-expression modules. Although GO enrichment ofthe whole list (180 genes) did not highlight any functional categories, analysis of the co-expressed genes resulted in enrichmentof the modules. This suggests that co-expression is a meaningful factor in exploring disease gene specificity.",
"A new functional gene network for human genesIn order to test the general ability of a gene network to prioritize disease genes, particularly in conjunction with GWAS studies, we constructed a genome-scale functional network of human genes, incorporating diverse expression, protein interaction, genetic interaction, sequence, literature, and comparative genomics data, including both data collected directly from human genes, as well as that from orthologous genes of yeast, worm, and fly.The resulting HumanNet gene network can be accessed through a web interface (http://www.functionalnet.org/humannet).Using this interface, researchers can easily search the network using a set of ''seed'' Network-guided genome-wide association mining genes of interest.The interface returns a list of genes ranked according to their connections to the seed genes, together with the evidence used to identify each coupling.The interactions and evidence can be downloaded, and a network visualization tool has been incorporated.All linkages can also be downloaded for independent analysis.",
"As mentioned previously, GeneNetwork(www.genenetwork.org) is a collaborative Web-based resource equipped with tools andfeatures for studying gene/gene and exploring genetic correlates to neurobehavioralphenotypes (Chesler et al. , 2003, 2004). The Web site is home to a growing collection ofgene expression and phenotypic data from a variety of species and brain regions, with a hostof links to external resources for tracing the interrelationships of a gene among multipleWeb-based resources. GeneNetwork also offers a number of correlation and mappingstrategies for assessing associations among multiple genes and QTLs.",
"It is possible for agene to play an important role in relevant networks, although geneticvariation, specifically, may not contribute to the genes association withthe network. Protein-protein interactions and expression correlationchanges might be more important drivers for inclusion of such a gene in agiven network. Furthermore, the genetic variation in other genesassociated with the same pathway may confer the relevance of the overallnetwork.",
"GeneNetwork has a function that constructs such association networks using either phenotype or transcript abundance, or indeed both simultaneously. It provides avisualization of the relative positions and numbers of possible interacting partners, how they interact (positive ornegative correlation) and in some situations, based onprior knowledge, it may suggest the directionality of theinteraction. An association network using principal component scorescalculated using a selected set of malting quality andyield-related trait data as variables provides an overview ofthe key barley traits that segregate in the St/Mx population(Figure 3, Additional File 3).",
"Network-Based ApproachesBased on these large-scale molecular interactions data, such as protein-protein interactions (PPIs), genetic interactions, TF-target interactions, and miRNA-target interactions, molecular networks can be used to visualize the relationships among a gene set, with genes represented as nodes and their molecular interactions as edges.Topological features of a network can often reveal the most critical regulators as hubs, or nodes with the most links, and the functional units/neighborhood among genes as the network modules, within which nodes are densely connected and in between which the nodes are relatively loosely connected.",
"GeneNetwork.org also offers a powerful statistical platform foronline network analyses and mapping, enabling numerous molecular questions to be probed in one centralized location(Chesler et al. , 2003, 2005; Li et al. , 2010; Mulligan et al. , 2012,2017, 2019). Most data are from groups of animals or humanswho have been fully genotyped or even sequenced. As a result, itcan be used to model causal networks that link DNA differencesto traits such as differences in expression, cell number, volumes,and behavior using real-time computation and graphing.",
"These different sources of interactiondata can be collated into network models (see Note 1) whichallow analysis using techniques borrowed from graph theory. Klaus Schughart and Robert W. Williams (eds. ), Systems Genetics: Methods and Protocols, Methods in Molecular Biology, vol. 1488,DOI 10.1007/978-1-4939-6427-7_10, Springer Science+Business Media New York 2017239240Rupert W. OverallAn important advantage of a network representation over a simplelisting of genes correlating to a phenotype is that the interactionsbetween the genes are also taken into account."
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