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

AI Article Synopsis

  • iModulonDB is a centralized database launched in 2020, focusing on iModulons—sets of co-expressed genes identified through independent component analysis of transcriptomic data, enhancing our understanding of transcriptional regulatory networks in organisms.
  • The recent update significantly expands the database, adding 19 new ICA decompositions, over 8,900 expression profiles, and features for 12 additional organisms, making it a more comprehensive resource for researchers.
  • New tools, interactive graphs, and improved interfaces facilitate user engagement and analysis of genetic regulation, allowing scientists to quickly access information regarding experimental conditions and explore related resources.

Article 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.

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Source
http://dx.doi.org/10.1093/nar/gkae1009DOI Listing

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