ArticlePLoS biology2007
Large-scale mapping and validation of Escherichia coli transcriptional regulation from a compendium of expression profiles.
Article in PLoS biology, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 742 papers, 1 of them a synthesis that pooled it.
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Who cites it
742 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Guidelines for bioinformatics of single-cell sequencing data analysis in Alzheimer's disease: review, recommendation, implementation and application.Molecular neurodegeneration · 2022Pooled it
- Integrative Bulk and Single-Cell Profiling of Premanufacture T-cell Populations Reveals Factors Mediating Long-Term Persistence of CAR T-cell Therapy.Cancer discovery · 2021Trial
- Artificial Intelligence for Plant Gene Regulatory Networks.International journal of molecular sciences · 2026Review
- OpenChallenges: A FAIR-aligned, centralized platform for crowdsourced challenges in biomedical research.Patterns (New York, N.Y.) · 2026Article
- SignifiKANTE: efficient P-value computation for gene regulatory networks.Bioinformatics (Oxford, England) · 2026Article
- Tensor network-based gene regulatory network inference for single-cell transcriptomic data.iScience · 2026Article
- Large-scale, interpretable gene regulatory network inference through biologically informed matrix factorization.bioRxiv : the preprint server for biology · 2026Article
- CoReGRN: a context-aware post-processing framework for gene regulatory network inference revealing regulatory signatures in HIV-Leishmaniasis.BMC genomics · 2026Article
- A comprehensive survey on graph neural networks for gene regulatory network inference.Briefings in bioinformatics · 2026Review
- Prediction of parsimonious and temporally sensitive sets of cell fate engineering transcription factors with IMCell.bioRxiv : the preprint server for biology · 2026Article
- A New Mutual Information Estimator for Continuous Censored Variables.Entropy (Basel, Switzerland) · 2026Article
- Computational blueprints for cell fate programming.Stem cell reports · 2026Review
- Inferring gene-regulatory networks using epigenomic priors.iScience · 2026Article
- Dynamic heterogeneity in an E. coli stress response regulon mediates gene activation and antimicrobial peptide tolerance.Cell reports · 2026Article
- GRNFormer: accurate gene regulatory network inference using graph transformer.Bioinformatics (Oxford, England) · 2026Article
- Genomic diversification, adaptive convergence, and regulatory rewiring in aging Escherichia coli colonies.BMC microbiology · 2026Article
- Challenges and Opportunities in Single-Sample Network Modeling.bioRxiv : the preprint server for biology · 2026Article
- Multimodal bioinformatic analyses of genome-scale expression beyond gene-centric differential expression.Briefings in bioinformatics · 2026Review
- Navigating the landscape of direct cellular reprogramming with DiReG.NPJ systems biology and applications · 2026Article
- Revealing hidden regulatory dependencies: multi-perspective graph learning for single-cell gene regulatory network inference.Briefings in bioinformatics · 2026Article
682 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
9 authors.
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Abstract
Machine learning approaches offer the potential to systematically identify transcriptional regulatory interactions from a compendium of microarray expression profiles. However, experimental validation of the performance of these methods at the genome scale has remained elusive. Here we assess the global performance of four existing classes of inference algorithms using 445 Escherichia coli Affymetrix arrays and 3,216 known E. coli regulatory interactions from RegulonDB. We also developed and applied the context likelihood of relatedness (CLR) algorithm, a novel extension of the relevance networks class of algorithms. CLR demonstrates an average precision gain of 36% relative to the next-best performing algorithm. At a 60% true positive rate, CLR identifies 1,079 regulatory interactions, of which 338 were in the previously known network and 741 were novel predictions. We tested the predicted interactions for three transcription factors with chromatin immunoprecipitation, confirming 21 novel interactions and verifying our RegulonDB-based performance estimates. CLR also identified a regulatory link providing central metabolic control of iron transport, which we confirmed with real-time quantitative PCR. The compendium of expression data compiled in this study, coupled with RegulonDB, provides a valuable model system for further improvement of network inference algorithms using experimental data.
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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.