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Meningococcus genome informatics platform: a system for analyzing multilocus sequence typing data

The Meningococcus Genome Informatics Platform (MGIP) is a suite of computational tools for the analysis of multilocus sequence typing (MLST) data, at http://mgip.biology.gatech.edu. MLST is used to generate allelic profiles to characterize strains of Neisseria meningitidis, a major cause of bacteria...

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Detalles Bibliográficos
Autores principales: Katz, Lee S., Bolen, Chris R., Harcourt, Brian H., Schmink, Susanna, Wang, Xin, Kislyuk, Andrey, Taylor, Robert T., Mayer, Leonard W., Jordan, I. King
Formato: Texto
Lenguaje:English
Publicado: Oxford University Press 2009
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2703879/
https://www.ncbi.nlm.nih.gov/pubmed/19468047
http://dx.doi.org/10.1093/nar/gkp288
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author Katz, Lee S.
Bolen, Chris R.
Harcourt, Brian H.
Schmink, Susanna
Wang, Xin
Kislyuk, Andrey
Taylor, Robert T.
Mayer, Leonard W.
Jordan, I. King
author_facet Katz, Lee S.
Bolen, Chris R.
Harcourt, Brian H.
Schmink, Susanna
Wang, Xin
Kislyuk, Andrey
Taylor, Robert T.
Mayer, Leonard W.
Jordan, I. King
author_sort Katz, Lee S.
collection PubMed
description The Meningococcus Genome Informatics Platform (MGIP) is a suite of computational tools for the analysis of multilocus sequence typing (MLST) data, at http://mgip.biology.gatech.edu. MLST is used to generate allelic profiles to characterize strains of Neisseria meningitidis, a major cause of bacterial meningitis worldwide. Neisseria meningitidis strains are characterized with MLST as specific sequence types (ST) and clonal complexes (CC) based on the DNA sequences at defined loci. These data are vital to molecular epidemiology studies of N. meningitidis, including outbreak investigations and population biology. MGIP analyzes DNA sequence trace files, returns individual allele calls and characterizes the STs and CCs. MGIP represents a substantial advance over existing software in several respects: (i) ease of use—MGIP is user friendly, intuitive and thoroughly documented; (ii) flexibility—because MGIP is a website, it is compatible with any computer with an internet connection, can be used from any geographic location, and there is no installation; (iii) speed—MGIP takes just over one minute to process a set of 96 trace files; and (iv) expandability—MGIP has the potential to expand to more loci than those used in MLST and even to other bacterial species.
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spelling pubmed-27038792009-07-01 Meningococcus genome informatics platform: a system for analyzing multilocus sequence typing data Katz, Lee S. Bolen, Chris R. Harcourt, Brian H. Schmink, Susanna Wang, Xin Kislyuk, Andrey Taylor, Robert T. Mayer, Leonard W. Jordan, I. King Nucleic Acids Res Articles The Meningococcus Genome Informatics Platform (MGIP) is a suite of computational tools for the analysis of multilocus sequence typing (MLST) data, at http://mgip.biology.gatech.edu. MLST is used to generate allelic profiles to characterize strains of Neisseria meningitidis, a major cause of bacterial meningitis worldwide. Neisseria meningitidis strains are characterized with MLST as specific sequence types (ST) and clonal complexes (CC) based on the DNA sequences at defined loci. These data are vital to molecular epidemiology studies of N. meningitidis, including outbreak investigations and population biology. MGIP analyzes DNA sequence trace files, returns individual allele calls and characterizes the STs and CCs. MGIP represents a substantial advance over existing software in several respects: (i) ease of use—MGIP is user friendly, intuitive and thoroughly documented; (ii) flexibility—because MGIP is a website, it is compatible with any computer with an internet connection, can be used from any geographic location, and there is no installation; (iii) speed—MGIP takes just over one minute to process a set of 96 trace files; and (iv) expandability—MGIP has the potential to expand to more loci than those used in MLST and even to other bacterial species. Oxford University Press 2009-07-01 2009-05-25 /pmc/articles/PMC2703879/ /pubmed/19468047 http://dx.doi.org/10.1093/nar/gkp288 Text en © 2009 The Author(s) http://creativecommons.org/licenses/by-nc/2.0/uk/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Articles
Katz, Lee S.
Bolen, Chris R.
Harcourt, Brian H.
Schmink, Susanna
Wang, Xin
Kislyuk, Andrey
Taylor, Robert T.
Mayer, Leonard W.
Jordan, I. King
Meningococcus genome informatics platform: a system for analyzing multilocus sequence typing data
title Meningococcus genome informatics platform: a system for analyzing multilocus sequence typing data
title_full Meningococcus genome informatics platform: a system for analyzing multilocus sequence typing data
title_fullStr Meningococcus genome informatics platform: a system for analyzing multilocus sequence typing data
title_full_unstemmed Meningococcus genome informatics platform: a system for analyzing multilocus sequence typing data
title_short Meningococcus genome informatics platform: a system for analyzing multilocus sequence typing data
title_sort meningococcus genome informatics platform: a system for analyzing multilocus sequence typing data
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2703879/
https://www.ncbi.nlm.nih.gov/pubmed/19468047
http://dx.doi.org/10.1093/nar/gkp288
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