Please use this identifier to cite or link to this item:
https://doi.org/10.1186/1471-2164-15-S10-S10
DC Field | Value | |
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dc.title | GWAMAR: Genome-wide assessment of mutations associated with drug resistance in bacteria | |
dc.contributor.author | Wozniak, M | |
dc.contributor.author | Tiuryn, J | |
dc.contributor.author | Wong, L | |
dc.date.accessioned | 2020-10-27T11:10:54Z | |
dc.date.available | 2020-10-27T11:10:54Z | |
dc.date.issued | 2014 | |
dc.identifier.citation | Wozniak, M, Tiuryn, J, Wong, L (2014). GWAMAR: Genome-wide assessment of mutations associated with drug resistance in bacteria. BMC Genomics 15 : S10. ScholarBank@NUS Repository. https://doi.org/10.1186/1471-2164-15-S10-S10 | |
dc.identifier.issn | 14712164 | |
dc.identifier.uri | https://scholarbank.nus.edu.sg/handle/10635/181518 | |
dc.description.abstract | Background: Development of drug resistance in bacteria causes antibiotic therapies to be less effective and more costly. Moreover, our understanding of the process remains incomplete. One promising approach to improve our understanding of how resistance is being acquired is to use whole-genome comparative approaches for detection of drug resistance-associated mutations. Results: We present GWAMAR, a tool we have developed for detecting of drug resistance-associated mutations in bacteria through comparative analysis of whole-genome sequences. The pipeline of GWAMAR comprises several steps. First, for a set of closely related bacterial genomes, it employs eCAMBer to identify homologous gene families. Second, based on multiple alignments of the gene families, it identifies mutations among the strains of interest. Third, it calculates several statistics to identify which mutations are the most associated with drug resistance. Conclusions: Based on our analysis of two large datasets retrieved from publicly available data for M. tuberculosis, we identified a set of novel putative drug resistance-associated mutations. As a part of this work, we present also an application of our tool to detect putative compensatory mutations. © 2014 Wozniak et al. | |
dc.rights | Attribution 4.0 International | |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | |
dc.source | Unpaywall 20201031 | |
dc.subject | ciprofloxacin | |
dc.subject | ethambutol | |
dc.subject | isoniazid | |
dc.subject | levofloxacin | |
dc.subject | moxifloxacin | |
dc.subject | ofloxacin | |
dc.subject | pyrazinamide | |
dc.subject | quinoline derived antiinfective agent | |
dc.subject | rifampicin | |
dc.subject | streptomycin | |
dc.subject | antibiotic resistance | |
dc.subject | Article | |
dc.subject | bacterial genome | |
dc.subject | bacterial strain | |
dc.subject | multigene family | |
dc.subject | Mycobacterium tuberculosis | |
dc.subject | nonhuman | |
dc.subject | point mutation | |
dc.subject | algorithm | |
dc.subject | bacterial genome | |
dc.subject | comparative study | |
dc.subject | computer program | |
dc.subject | genetic association | |
dc.subject | genetic database | |
dc.subject | genetics | |
dc.subject | nucleotide sequence | |
dc.subject | phylogeny | |
dc.subject | procedures | |
dc.subject | statistical model | |
dc.subject | Algorithms | |
dc.subject | Databases, Genetic | |
dc.subject | DNA Mutational Analysis | |
dc.subject | Drug Resistance, Bacterial | |
dc.subject | Genome, Bacterial | |
dc.subject | Genome-Wide Association Study | |
dc.subject | Models, Statistical | |
dc.subject | Multigene Family | |
dc.subject | Mycobacterium tuberculosis | |
dc.subject | Phylogeny | |
dc.subject | Point Mutation | |
dc.subject | Software | |
dc.type | Article | |
dc.contributor.department | INSTITUTE OF SYSTEMS SCIENCE | |
dc.description.doi | 10.1186/1471-2164-15-S10-S10 | |
dc.description.sourcetitle | BMC Genomics | |
dc.description.volume | 15 | |
dc.description.page | S10 | |
Appears in Collections: | Elements Staff Publications |
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