ArticleBioinformatics (Oxford, England)2011
The role of indirect connections in gene networks in predicting function.
Article in Bioinformatics (Oxford, England), 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers, 2 of them syntheses that pooled it.
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Who cites it
43 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Network aggregation improves gene function prediction of grapevine gene co-expression networks.Plant molecular biology · 2020Pooled it
- Meta-analysis of gene coexpression networks in the post-mortem prefrontal cortex of patients with schizophrenia and unaffected controls.BMC neuroscience · 2013Pooled it
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- Defining the extent of gene function using ROC curvature.Bioinformatics (Oxford, England) · 2022Article
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- NOREVA: enhanced normalization and evaluation of time-course and multi-class metabolomic data.Nucleic acids research · 2020Article
- Prediction of seed gene function in progressive diabetic neuropathy by a network-based inference method.Experimental and therapeutic medicine · 2019Article
- Optimal pathways involved in the treatment of sevoflurane or propofol for patients undergoing coronary artery bypass graft surgery.Experimental and therapeutic medicine · 2019Article
- Prediction of key gene function in spinal muscular atrophy using guilt by association method based on network and gene ontology.Experimental and therapeutic medicine · 2019Article
- Constructing differential co-expression network to predict key pathways for myocardial infarction.Experimental and therapeutic medicine · 2019Article
- Differential coexpression in human tissues and the confounding effect of mean expression levels.Bioinformatics (Oxford, England) · 2019Article
- Identification of the defense-related geneHereditas · 2019Article
- Exploration of gene functions for esophageal squamous cell carcinoma using network-based guilt by association principle.Brazilian journal of medical and biological research = Revista brasileira de pesquisas medicas e biologica · 2018Article
- Identification of novel targets for multiple myeloma through integrative approach with Monte Carlo cross-validation analysis.Journal of bone oncology · 2017Article
- Construction and Optimization of a Large Gene Coexpression Network in Maize Using RNA-Seq Data.Plant physiology · 2017Article
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
motivationGene networks have been used widely in gene function prediction algorithms, many based on complex extensions of the 'guilt by association' principle. We sought to provide a unified explanation for the performance of gene function prediction algorithms in exploiting network structure and thereby simplify future analysis.
resultsWe use co-expression networks to show that most exploited network structure simply reconstructs the original correlation matrices from which the co-expression network was obtained. We show the same principle works in predicting gene function in protein interaction networks and that these methods perform comparably to much more sophisticated gene function prediction algorithms. AVAILABILITY AND IMPLEMENTATION: Data and algorithm implementation are fully described and available at http://www.chibi.ubc.ca/extended. Programs are provided in Matlab m-code. CONTACT: paul@chibi.ubc.ca
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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.