iModulonDB 2.0: dynamic tools to facilitate knowledge-mining and user-enabled analyses of curated transcriptomic datasets

iModulons-sets of co-expressed genes identified through independent component analysis (ICA) of high-quality transcriptomic datasets-provide an unbiased, modular view of an organism's transcriptional regulatory network. Established in 2020, iModulonDB (iModulonDB.org) serves as a centralized repository of curated iModulon sets, enabling users to explore iModulons and download the associated transcriptomic data. This update reflects a significant expansion of the database-19 new ICA decompositions (+633%) spanning 8 925 expression profiles (+1370%), 503 studies (+2290%) and 12 additional organisms (+400%)-and introduces new features to help scientists decipher the mechanisms governing prokaryotic transcriptional regulation. To facilitate comprehension of the underlying expression profiles, the updated user-interface displays essential information about each data-generating study (e.g. the experimental conditions and publication abstract). Dashboards now include condition-specific coloring and highlight data generated from genetically perturbed strains, enabling users to rapidly interpret disruptions in transcriptional regulation. New interactive graphs rapidly convey omics-derived indicators (e.g. the explained variance of ICA decompositions, genetic overlap between iModulons and regulons). Direct links to operon diagrams (BioCyc) and protein-protein interaction networks (STRING) provide users with seamless access to external resources for further assessment of iModulons. Lastly, a new suite of search-driven and species-wide analysis tools promotes user-engagement with iModulons, reinforcing iModulonDB's role as a dynamic, interactive knowledgebase of prokaryotic transcriptional regulation.

Authors

Institutions

Publication Details

Journal
Nucleic Acids Research
Published
2024-11-04
DOI
https://doi.org/10.1093/nar/gkae1009
Citations
24
Primary Topic
Gene expression and cancer classification
Type
article
Field-Weighted Citation Impact
5.61

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

iModulonDB 2.0: dynamic tools to facilitate knowledge-mining and user-enabled analyses of curated transcriptomic datasets

Jayanth Krishnan, Arjun Patel, Edward Catoiu, Gaoyuan Li et al.
24 citations
Nucleic Acids Research
Gene expression and cancer classification
5.61
article

iModulonDB 2.0: dynamic tools to facilitate knowledge-mining and user-enabled analyses of curated transcriptomic datasets

Jayanth Krishnan, Arjun Patel, Edward Catoiu, Gaoyuan Li, Bernhard Ø. Palsson, Yuan Yuan, Donghui Choe, Daniel C. Zielinski, Patrick V. Phaneuf, Jongoh Shin, Jeffrey T. A. Burrows, Kevin Rychel, Heera Bajpe, Xiaoying Lou
article en
24 citations

Abstract

iModulons-sets of co-expressed genes identified through independent component analysis (ICA) of high-quality transcriptomic datasets-provide an unbiased, modular view of an organism's transcriptional regulatory network. Established in 2020, iModulonDB (iModulonDB.org) serves as a centralized repository of curated iModulon sets, enabling users to explore iModulons and download the associated transcriptomic data. This update reflects a significant expansion of the database-19 new ICA decompositions (+633%) spanning 8 925 expression profiles (+1370%), 503 studies (+2290%) and 12 additional organisms (+400%)-and introduces new features to help scientists decipher the mechanisms governing prokaryotic transcriptional regulation. To facilitate comprehension of the underlying expression profiles, the updated user-interface displays essential information about each data-generating study (e.g. the experimental conditions and publication abstract). Dashboards now include condition-specific coloring and highlight data generated from genetically perturbed strains, enabling users to rapidly interpret disruptions in transcriptional regulation. New interactive graphs rapidly convey omics-derived indicators (e.g. the explained variance of ICA decompositions, genetic overlap between iModulons and regulons). Direct links to operon diagrams (BioCyc) and protein-protein interaction networks (STRING) provide users with seamless access to external resources for further assessment of iModulons. Lastly, a new suite of search-driven and species-wide analysis tools promotes user-engagement with iModulons, reinforcing iModulonDB's role as a dynamic, interactive knowledgebase of prokaryotic transcriptional regulation.

Nucleic Acids ResearchVol. 53(D1)
Novo Nordisk Foundation (DK), University of California San Diego (US), Technical University of Denmark (DK)
Novo Nordisk, Novo Nordisk Fonden, National Institutes of Health
Openalex Percentile: Top 3%
Gene expression and cancer classification
5.61
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.