Towards better prediction of Mycobacterium tuberculosis lineages from MIRU-VNTR data.
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| Title: | Towards better prediction of Mycobacterium tuberculosis lineages from MIRU-VNTR data. |
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| Authors: | Thain N; School of Computing Science, Simon Fraser University, Burnaby, BC, Canada., Le C; School of Computing Science, Simon Fraser University, Burnaby, BC, Canada., Crossa A; New York City Department of Health and Mental Hygiene, Queens, NY, USA., Ahuja SD; New York City Department of Health and Mental Hygiene, Queens, NY, USA., Meissner JS; New York City Department of Health and Mental Hygiene, Queens, NY, USA., Mathema B; Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, USA., Kreiswirth B; Public Health Research Institute TB Center, Rutgers University, Newark, NJ, USA., Kurepina N; Public Health Research Institute TB Center, Rutgers University, Newark, NJ, USA., Cohen T; Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA., Chindelevitch L; School of Computing Science, Simon Fraser University, Burnaby, BC, Canada. Electronic address: leonid@sfu.ca. |
| Source: | Infection, genetics and evolution : journal of molecular epidemiology and evolutionary genetics in infectious diseases [Infect Genet Evol] 2019 Aug; Vol. 72, pp. 59-66. Date of Electronic Publication: 2018 Jun 28. |
| Publication Type: | Journal Article; Research Support, N.I.H., Extramural; Research Support, Non-U.S. Gov't |
| Journal Info: | Publisher: Elsevier Science Country of Publication: Netherlands NLM ID: 101084138 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1567-7257 (Electronic) Linking ISSN: 15671348 NLM ISO Abbreviation: Infect Genet Evol Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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