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Conference Paper: Deep analysis and optimization of CARD antibiotic resistance gene discovery models

TitleDeep analysis and optimization of CARD antibiotic resistance gene discovery models
Authors
KeywordsAntibiotic resistance gene
CARD database
RND efflux pumps
Issue Date2019
PublisherBioMed Central Ltd. The Journal's web site is located at http://www.biomedcentral.com/bmcgenomics/
Citation
Proceedings of the Joint International GIW & ABACBS-2019 Conference: genomics, Sydney, Australia, 9-11 December 2019. In BMC Genomics, v. 20 n. suppl. 10, p. article no. 914 How to Cite?
AbstractBackground: Identification of antibiotic resistance genes from environmental samples has been a critical sub-domain of gene discovery which is directly connected to human health. However, it is drawing extraordinary attention in recent years and regarded as a severe threat to human health by many institutions around the world. To satisfy the needs for efficient ARG discovery, a series of online antibiotic resistance gene databases have been published. This article will conduct an in-depth analysis of CARD, one of the most widely used ARG databases. Results: The decision model of CARD is based the alignment score with a single ARG type. We discover the occasions where the model is likely to make false prediction, and then propose an optimization method on top of the current CARD model. The optimization is expected to raise the coherence with BLAST homology relationships and improve the confidence for identification of ARGs using the database. Conclusions: The absence of public recognized benchmark makes it challenging to evaluate the performance of ARG identification. However, possible wrong predictions and methods for resolving the problem can be inferred by computational analysis of the identification method and the underlying reference sequences. We hope our work can bring insight to the mission of precise ARG type classifications.
Persistent Identifierhttp://hdl.handle.net/10722/287585
ISSN
2019 Impact Factor: 3.594
2015 SCImago Journal Rankings: 2.343
PubMed Central ID
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorYao, H-
dc.contributor.authorYiu, SM-
dc.date.accessioned2020-10-05T12:00:13Z-
dc.date.available2020-10-05T12:00:13Z-
dc.date.issued2019-
dc.identifier.citationProceedings of the Joint International GIW & ABACBS-2019 Conference: genomics, Sydney, Australia, 9-11 December 2019. In BMC Genomics, v. 20 n. suppl. 10, p. article no. 914-
dc.identifier.issn1471-2164-
dc.identifier.urihttp://hdl.handle.net/10722/287585-
dc.description.abstractBackground: Identification of antibiotic resistance genes from environmental samples has been a critical sub-domain of gene discovery which is directly connected to human health. However, it is drawing extraordinary attention in recent years and regarded as a severe threat to human health by many institutions around the world. To satisfy the needs for efficient ARG discovery, a series of online antibiotic resistance gene databases have been published. This article will conduct an in-depth analysis of CARD, one of the most widely used ARG databases. Results: The decision model of CARD is based the alignment score with a single ARG type. We discover the occasions where the model is likely to make false prediction, and then propose an optimization method on top of the current CARD model. The optimization is expected to raise the coherence with BLAST homology relationships and improve the confidence for identification of ARGs using the database. Conclusions: The absence of public recognized benchmark makes it challenging to evaluate the performance of ARG identification. However, possible wrong predictions and methods for resolving the problem can be inferred by computational analysis of the identification method and the underlying reference sequences. We hope our work can bring insight to the mission of precise ARG type classifications.-
dc.languageeng-
dc.publisherBioMed Central Ltd. The Journal's web site is located at http://www.biomedcentral.com/bmcgenomics/-
dc.relation.ispartofBMC Genomics-
dc.rightsBMC Genomics. Copyright © BioMed Central Ltd.-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.subjectAntibiotic resistance gene-
dc.subjectCARD database-
dc.subjectRND efflux pumps-
dc.titleDeep analysis and optimization of CARD antibiotic resistance gene discovery models-
dc.typeConference_Paper-
dc.identifier.emailYao, H: viphbyao@hku.hk-
dc.identifier.emailYiu, SM: smyiu@cs.hku.hk-
dc.identifier.authorityYiu, SM=rp00207-
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1186/s12864-019-6318-5-
dc.identifier.pmid31888459-
dc.identifier.pmcidPMC6936150-
dc.identifier.scopuseid_2-s2.0-85077187728-
dc.identifier.hkuros315383-
dc.identifier.volume20-
dc.identifier.issuesuppl. 10-
dc.identifier.spagearticle no. 914-
dc.identifier.epagearticle no. 914-
dc.identifier.eissn1471-2164-
dc.identifier.isiWOS:000508013000002-
dc.publisher.placeUnited Kingdom-
dc.identifier.issnl1471-2164-

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