ArticlePLoS computational biology2021
Independent component analysis recovers consistent regulatory signals from disparate datasets.
Article in PLoS computational biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.
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Who cites it
26 citing papers in PubMed.
- Review
- A systems-level atlas of carbon-response transcriptional states inProceedings of the National Academy of Sciences of the United States of America · 2026Article
- Minimal gene signatures enable high-accuracy prediction of antibiotic resistance in Pseudomonas aeruginosa.NPJ systems biology and applications · 2025Article
- Unsupervised discovery of clinical disease signatures using probabilistic independence.Journal of biomedical informatics · 2025Article
- Modulating bacterial function utilizing A knowledge base of transcriptional regulatory modules.Nucleic acids research · 2024Article
- iModulonMiner and PyModulon: Software for unsupervised mining of gene expression compendia.PLoS computational biology · 2024Article
- CyuR is a dual regulator for L-cysteine dependent antimicrobial resistance in Escherichia coli.Communications biology · 2024Article
- Proteome allocation is linked to transcriptional regulation through a modularized transcriptome.Nature communications · 2024Article
- Machine learning analysis of RB-TnSeq fitness data predicts functional gene modules inmSystems · 2024Article
- High-resolution temporal profiling of E. coli transcriptional response.Nature communications · 2023Article
- A multi-scale expression and regulation knowledge base for Escherichia coli.Nucleic acids research · 2023Article
- Machine learning uncovers themSystems · 2023Article
- Genome-wide promoter responses to CRISPR perturbations of regulators reveal regulatory networks in Escherichia coli.Nature communications · 2023Article
- Independent Component Analysis Reveals the Transcriptional Regulatory Modules inInternational journal of molecular sciences · 2023Article
- Elucidation of independently modulated genes inmSystems · 2023Article
- Proteome allocation is linked to transcriptional regulation through a modularized transcriptome.bioRxiv : the preprint server for biology · 2023Article
- Two novel genes identified by large-scale transcriptomic analysis are essential for biofilm and rugose colony development of Vibrio vulnificus.PLoS pathogens · 2023Article
- Article
- GenomicSuperSignature facilitates interpretation of RNA-seq experiments through robust, efficient comparison to public databases.Nature communications · 2022Article
- Expanding the search for small-molecule antibacterials by multidimensional profiling.Nature chemical biology · 2022Review
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The availability of bacterial transcriptomes has dramatically increased in recent years. This data deluge could result in detailed inference of underlying regulatory networks, but the diversity of experimental platforms and protocols introduces critical biases that could hinder scalable analysis of existing data. Here, we show that the underlying structure of the E. coli transcriptome, as determined by Independent Component Analysis (ICA), is conserved across multiple independent datasets, including both RNA-seq and microarray datasets. We subsequently combined five transcriptomics datasets into a large compendium containing over 800 expression profiles and discovered that its underlying ICA-based structure was still comparable to that of the individual datasets. With this understanding, we expanded our analysis to over 3,000 E. coli expression profiles and predicted three high-impact regulons that respond to oxidative stress, anaerobiosis, and antibiotic treatment. ICA thus enables deep analysis of disparate data to uncover new insights that were not visible in the individual datasets.
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