ArticlePLoS computational biology2012
"Guilt by association" is the exception rather than the rule in gene networks.
Article in PLoS computational biology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 124 papers, 3 of them syntheses that pooled it.
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Who cites it
124 citing papers in PubMed, 3 syntheses or guidelines pooled it, 222 citations in OpenAlex.
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- Accurate prediction of drug-protein interactions by maintaining the original topological relationships among embeddings.BMC biology · 2025Article
- Utilizing RNA-seq data in monotone iterative generalized linear model to elevate prior knowledge quality of the circRNA-miRNA-mRNA regulatory axis.BMC bioinformatics · 2025Article
- Transcriptional and functional characterization in the terpenoid precursor pathway of the early land plant Physcomitrium patens.Plant biology (Stuttgart, Germany) · 2025Article
- VI-VS: calibrated identification of feature dependencies in single-cell multiomics.Genome biology · 2024Article
- Blood-derived microRNAs are related to cognitive domains in the general population.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2024Article
- Fibrinaloid Microclots and Atrial Fibrillation.Biomedicines · 2024Review
- Hypothesis generation for rare and undiagnosed diseases through clustering and classifying time-versioned biological ontologies.PloS one · 2024Article
- Multiomic interpretation of fungus-infected ant metabolomes during manipulated summit disease.Scientific reports · 2023Article
- Using machine learning to predict protein-protein interactions between a zombie ant fungus and its carpenter ant host.Scientific reports · 2023Article
- Distinction between rhinitis alone and rhinitis with asthma using interactomics.Scientific reports · 2023Article
64 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
Gene networks are commonly interpreted as encoding functional information in their connections. An extensively validated principle called guilt by association states that genes which are associated or interacting are more likely to share function. Guilt by association provides the central top-down principle for analyzing gene networks in functional terms or assessing their quality in encoding functional information. In this work, we show that functional information within gene networks is typically concentrated in only a very few interactions whose properties cannot be reliably related to the rest of the network. In effect, the apparent encoding of function within networks has been largely driven by outliers whose behaviour cannot even be generalized to individual genes, let alone to the network at large. While experimentalist-driven analysis of interactions may use prior expert knowledge to focus on the small fraction of critically important data, large-scale computational analyses have typically assumed that high-performance cross-validation in a network is due to a generalizable encoding of function. Because we find that gene function is not systemically encoded in networks, but dependent on specific and critical interactions, we conclude it is necessary to focus on the details of how networks encode function and what information computational analyses use to extract functional meaning. We explore a number of consequences of this and find that network structure itself provides clues as to which connections are critical and that systemic properties, such as scale-free-like behaviour, do not map onto the functional connectivity within networks.
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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.