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
- Jayanth Krishnan
- Arjun Patel (ORCID: https://orcid.org/0000-0003-1959-0445)
- Edward Catoiu (ORCID: https://orcid.org/0000-0001-8680-7291)
- Gaoyuan Li (ORCID: https://orcid.org/0009-0003-4392-0966)
- Bernhard Ø. Palsson (ORCID: https://orcid.org/0000-0003-2357-6785)
- Yuan Yuan (ORCID: https://orcid.org/0000-0002-9509-9167)
- Donghui Choe (ORCID: https://orcid.org/0000-0003-1107-7380)
- Daniel C. Zielinski (ORCID: https://orcid.org/0000-0001-6452-483X)
- Patrick V. Phaneuf (ORCID: https://orcid.org/0000-0002-4122-6589)
- Jongoh Shin (ORCID: https://orcid.org/0000-0002-5094-1912)
- Jeffrey T. A. Burrows (ORCID: https://orcid.org/0000-0001-6595-8736)
- Kevin Rychel (ORCID: https://orcid.org/0000-0002-4769-2804)
- Heera Bajpe
- Xiaoying Lou (ORCID: https://orcid.org/0000-0003-4847-5649)
Institutions
- Novo Nordisk Foundation (DK)
- University of California San Diego (US)
- Technical University of Denmark (DK)
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
- Novo Nordisk
- Novo Nordisk Fonden
- National Institutes of Health