<HashMap><database>biostudies-literature</database><scores/><additional><omics_type>Unknown</omics_type><volume>18</volume><submitter>Escorcia-Rodriguez JM</submitter><funding>Dirección General de Asuntos del Personal Académico, Universidad Nacional Autónoma de México</funding><pubmed_abstract>Some organism-specific databases about regulation in bacteria have become larger, accelerated by high-throughput methodologies, while others are no longer updated or accessible. Each database homogenize its datasets, giving rise to heterogeneity across databases. Such heterogeneity mainly encompasses different names for a gene and different network representations, generating duplicated interactions that could bias network analyses. Abasy (&lt;b>A&lt;/b>cross-&lt;b>ba&lt;/b>cteria &lt;b>sy&lt;/b>stems) Atlas consolidates information from different sources into meta-curated regulatory networks in bacteria. The high-quality networks in Abasy Atlas enable cross-organisms analyses, such as benchmarking studies where gold standards are required. Nevertheless, network incompleteness still casts doubts on the conc</pubmed_abstract><journal>Computational and structural biotechnology journal</journal><pagination>1228-1237</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC7283102</full_dataset_link><repository>biostudies-literature</repository><pubmed_title>Abasy Atlas v2.2: The most comprehensive and up-to-date inventory of meta-curated, historical, bacterial regulatory networks, their completeness and system-level characterization.</pubmed_title><pmcid>PMC7283102</pmcid><pubmed_authors>Escorcia-Rodriguez JM</pubmed_authors><pubmed_authors>Freyre-Gonzalez JA</pubmed_authors><pubmed_authors>Tauch A</pubmed_authors></additional><is_claimable>false</is_claimable><name>Abasy Atlas v2.2: The most comprehensive and up-to-date inventory of meta-curated, historical, bacterial regulatory networks, their completeness and system-level characterization.</name><description>Some organism-specific databases about regulation in bacteria have become larger, accelerated by high-throughput methodologies, while others are no longer updated or accessible. Each database homogenize its datasets, giving rise to heterogeneity across databases. Such heterogeneity mainly encompasses different names for a gene and different network representations, generating duplicated interactions that could bias network analyses. Abasy (&lt;b>A&lt;/b>cross-&lt;b>ba&lt;/b>cteria &lt;b>sy&lt;/b>stems) Atlas consolidates information from different sources into meta-curated regulatory networks in bacteria. The high-quality networks in Abasy Atlas enable cross-organisms analyses, such as benchmarking studies where gold standards are required. Nevertheless, network incompleteness still casts doubts on the conc</description><dates><release>2020-01-01T00:00:00Z</release><publication>2020</publication><modification>2026-07-15T22:09:38.596Z</modification><creation>2026-07-09T10:20:57.821Z</creation></dates><accession>S-EPMC7283102</accession><cross_references><pubmed>32542109</pubmed><doi>10.1016/j.csbj.2020.05.015</doi></cross_references></HashMap>