ArticleGenome research2010
Predicting genetic modifier loci using functional gene networks.
Article in Genome research, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 47 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
47 citing papers in PubMed.
- Exploiting Cancer Synthetic Lethality in Cancer-Lessons Learnt from PARP Inhibitors.Cancer treatment and research · 2023Article
- Incomplete Penetrance and Variable Expressivity: From Clinical Studies to Population Cohorts.Frontiers in genetics · 2022Review
- A functionally defined high-density NRF2 interactome reveals new conditional regulators of ARE transactivation.Redox biology · 2020Article
- Responsible, practical genomic data sharing that accelerates research.Nature reviews. Genetics · 2020Review
- Identification and characterization of differentially expressed genes in Caenorhabditis elegans in response to pathogenic and nonpathogenic Stenotrophomonas maltophilia.BMC microbiology · 2020Article
- Genetic Modifiers and Rare Mendelian Disease.Genes · 2020Review
- Using deep learning to model the hierarchical structure and function of a cell.Nature methods · 2018Article
- Using WormBase: A Genome Biology Resource for Caenorhabditis elegans and Related Nematodes.Methods in molecular biology (Clifton, N.J.) · 2018Article
- Transcriptomic, Functional, and Network Analyses Reveal Novel Genes Involved in the Interaction BetweenFrontiers in cellular and infection microbiology · 2018Article
- Taxonomically Restricted Genes with Essential Functions Frequently Play Roles in Chromosome Segregation inG3 (Bethesda, Md.) · 2017Article
- Ras/MAPK Modifier Loci Revealed by eQTL inG3 (Bethesda, Md.) · 2017Article
- Predictability of Genetic Interactions from Functional Gene Modules.G3 (Bethesda, Md.) · 2017Article
- PoplarGene: poplar gene network and resource for mining functional information for genes from woody plants.Scientific reports · 2016Article
- Algorithms for modeling global and context-specific functional relationship networks.Briefings in bioinformatics · 2016Article
- Overlapping cell population expression profiling and regulatory inference in C. elegans.BMC genomics · 2016Article
- Translation of Genotype to Phenotype by a Hierarchy of Cell Subsystems.Cell systems · 2016Article
- Structural and Functional Characterization of a Caenorhabditis elegans Genetic Interaction Network within Pathways.PLoS computational biology · 2016Article
- Recent Advances and Emerging Applications in Text and Data Mining for Biomedical Discovery.Briefings in bioinformatics · 2016Review
- Associations of SNPs located at candidate genes to bovine growth traits, prioritized with an interaction networks construction approach.BMC genetics · 2015Article
- Yeast Phenomics: An Experimental Approach for Modeling Gene Interaction Networks that Buffer Disease.Genes · 2015Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
Most phenotypes are genetically complex, with contributions from mutations in many different genes. Mutations in more than one gene can combine synergistically to cause phenotypic change, and systematic studies in model organisms show that these genetic interactions are pervasive. However, in human association studies such nonadditive genetic interactions are very difficult to identify because of a lack of statistical power--simply put, the number of potential interactions is too vast. One approach to resolve this is to predict candidate modifier interactions between loci, and then to specifically test these for associations with the phenotype. Here, we describe a general method for predicting genetic interactions based on the use of integrated functional gene networks. We show that in both Saccharomyces cerevisiae and Caenorhabditis elegans a single high-coverage, high-quality functional network can successfully predict genetic modifiers for the majority of genes. For C. elegans we also describe the construction of a new, improved, and expanded functional network, WormNet 2. Using this network we demonstrate how it is possible to rapidly expand the number of modifier loci known for a gene, predicting and validating new genetic interactions for each of three signal transduction genes. We propose that this approach, termed network-guided modifier screening, provides a general strategy for predicting genetic interactions. This work thus suggests that a high-quality integrated human gene network will provide a powerful resource for modifier locus discovery in many different diseases.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.