<HashMap><database>biostudies-literature</database><scores/><additional><submitter>Alcock BP</submitter><funding>NSERC</funding><funding>David Braley Chair in Computational Biology</funding><funding>Visual and Automated Disease Analytics graduate training program</funding><funding>Canadian Institutes of Health Research</funding><funding>Simon Fraser University</funding><funding>Michael G. DeGroote Centre for Medicinal Cannabis Research</funding><funding>CIHR</funding><funding>Cisco Research Chair in Bioinformatics</funding><funding>Michael G. DeGroote Institute for Infectious Disease Research</funding><funding>Ontario Graduate Scholarship, McMaster University&amp;apos;s MacDATA Institute Graduate Fellowship</funding><funding>Ontario Graduate Scholarship</funding><funding>Fred and Helen Knight Enrichment Award</funding><funding>Canada Foundation for Innovation</funding><funding>CIHR Canada Graduate Scholarship</funding><funding>Ontario Research Fund</funding><funding>Genome Canada</funding><funding>Ontario Graduate Scholarship, MacData Institute Graduate Fellowship, Ashbaugh Graduate Scholarship</funding><funding>McMaster Service Lab and Repository computing cluster</funding><pagination>D690-D699</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC9825576</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>51(D1)</volume><pubmed_abstract>The Comprehensive Antibiotic Resistance Database (CARD; card.mcmaster.ca) combines the Antibiotic Resistance Ontology (ARO) with curated AMR gene (ARG) sequences and resistance-conferring mutations to provide an informatics framework for annotation and interpretation of resistomes. As of version 3.2.4, CARD encompasses 6627 ontology terms, 5010 reference sequences, 1933 mutations, 3004 publications, and 5057 AMR detection models that can be used by the accompanying Resistance Gene Identifier (RGI) software to annotate genomic or metagenomic sequences. Focused curation enhancements since 2020 include expanded β-lactamase curation, incorporation of likelihood-based AMR mutations for Mycobacterium tuberculosis, addition of disinfectants and antiseptics plus their associated ARGs, and systemat</pubmed_abstract><journal>Nucleic acids research</journal><pubmed_title>CARD 2023: expanded curation, support for machine learning, and resistome prediction at the Comprehensive Antibiotic Resistance Database.</pubmed_title><pmcid>PMC9825576</pmcid><funding_grant_id>FRN 143215</funding_grant_id><funding_grant_id>PJT-159456</funding_grant_id><funding_grant_id>RE09-047</funding_grant_id><pubmed_authors>Smith KW</pubmed_authors><pubmed_authors>French S</pubmed_authors><pubmed_authors>Liang ZC</pubmed_authors><pubmed_authors>Jia B</pubmed_authors><pubmed_authors>Carfrae LA</pubmed_authors><pubmed_authors>Bhando T</pubmed_authors><pubmed_authors>Maguire F</pubmed_authors><pubmed_authors>Dooley D</pubmed_authors><pubmed_authors>Edalatmand A</pubmed_authors><pubmed_authors>Golbon B</pubmed_authors><pubmed_authors>Brown ED</pubmed_authors><pubmed_authors>Petkau A</pubmed_authors><pubmed_authors>Tsang KK</pubmed_authors><pubmed_authors>Jiang X</pubmed_authors><pubmed_authors>Brinkman FSL</pubmed_authors><pubmed_authors>Mukiri KM</pubmed_authors><pubmed_authors>Alcock BP</pubmed_authors><pubmed_authors>Huynh W</pubmed_authors><pubmed_authors>McCarthy MC</pubmed_authors><pubmed_authors>Kwong M</pubmed_authors><pubmed_authors>Shan P</pubmed_authors><pubmed_authors>Hsiao WWL</pubmed_authors><pubmed_authors>Nasir JA</pubmed_authors><pubmed_authors>Bordeleau E</pubmed_authors><pubmed_authors>Van Domselaar G</pubmed_authors><pubmed_authors>Baker SJC</pubmed_authors><pubmed_authors>Chalil R</pubmed_authors><pubmed_authors>McArthur AG</pubmed_authors><pubmed_authors>Wlodarski MA</pubmed_authors><pubmed_authors>Niu KC</pubmed_authors><pubmed_authors>Yang JYJ</pubmed_authors><pubmed_authors>Tu MM</pubmed_authors><pubmed_authors>Beiko RG</pubmed_authors><pubmed_authors>Dave M</pubmed_authors><pubmed_authors>Hoad GR</pubmed_authors><pubmed_authors>Gray KL</pubmed_authors><pubmed_authors>Rachwalski K</pubmed_authors><pubmed_authors>Zubyk HL</pubmed_authors><pubmed_authors>Syed SA</pubmed_authors><pubmed_authors>Kaur K</pubmed_authors><pubmed_authors>Raphenya AR</pubmed_authors><pubmed_authors>Farha MA</pubmed_authors><pubmed_authors>Gordzevich R</pubmed_authors><pubmed_authors>Imtiaz H</pubmed_authors><pubmed_authors>Griffiths E</pubmed_authors></additional><is_claimable>false</is_claimable><name>CARD 2023: expanded curation, support for machine learning, and resistome prediction at the Comprehensive Antibiotic Resistance Database.</name><description>The Comprehensive Antibiotic Resistance Database (CARD; card.mcmaster.ca) combines the Antibiotic Resistance Ontology (ARO) with curated AMR gene (ARG) sequences and resistance-conferring mutations to provide an informatics framework for annotation and interpretation of resistomes. As of version 3.2.4, CARD encompasses 6627 ontology terms, 5010 reference sequences, 1933 mutations, 3004 publications, and 5057 AMR detection models that can be used by the accompanying Resistance Gene Identifier (RGI) software to annotate genomic or metagenomic sequences. Focused curation enhancements since 2020 include expanded β-lactamase curation, incorporation of likelihood-based AMR mutations for Mycobacterium tuberculosis, addition of disinfectants and antiseptics plus their associated ARGs, and systemat</description><dates><release>2023-01-01T00:00:00Z</release><publication>2023 Jan</publication><modification>2025-08-24T03:08:22.461Z</modification><creation>2025-04-05T17:01:47.852Z</creation></dates><accession>S-EPMC9825576</accession><cross_references><pubmed>36263822</pubmed><doi>10.1093/nar/gkac920</doi></cross_references></HashMap>