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Specialized Hidden Markov Model Databases for Microbial Genomics
As hidden Markov models (HMMs) become increasingly more important in the analysis of biological sequences, so too have databases of HMMs expanded in size, number and importance. While the standard paradigm a short while ago was the analysis of one or a few sequences at a time, it has now become stan...
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Formato: | Texto |
Lenguaje: | English |
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Hindawi Publishing Corporation
2003
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2447419/ https://www.ncbi.nlm.nih.gov/pubmed/18629132 http://dx.doi.org/10.1002/cfg.280 |
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author | Gollery, Martin |
author_facet | Gollery, Martin |
author_sort | Gollery, Martin |
collection | PubMed |
description | As hidden Markov models (HMMs) become increasingly more important in the analysis of biological sequences, so too have databases of HMMs expanded in size, number and importance. While the standard paradigm a short while ago was the analysis of one or a few sequences at a time, it has now become standard procedure to submit an entire microbial genome. In the future, it will be common to submit large groups of completed genomes to run simultaneously against a dozen public databases and any number of internally developed targets. This paper looks at some of the readily available HMM (or HMM-like) algorithms and several publicly available HMM databases, and outlines methods by which the reader may develop custom HMM targets. |
format | Text |
id | pubmed-2447419 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2003 |
publisher | Hindawi Publishing Corporation |
record_format | MEDLINE/PubMed |
spelling | pubmed-24474192008-07-14 Specialized Hidden Markov Model Databases for Microbial Genomics Gollery, Martin Comp Funct Genomics Research Article As hidden Markov models (HMMs) become increasingly more important in the analysis of biological sequences, so too have databases of HMMs expanded in size, number and importance. While the standard paradigm a short while ago was the analysis of one or a few sequences at a time, it has now become standard procedure to submit an entire microbial genome. In the future, it will be common to submit large groups of completed genomes to run simultaneously against a dozen public databases and any number of internally developed targets. This paper looks at some of the readily available HMM (or HMM-like) algorithms and several publicly available HMM databases, and outlines methods by which the reader may develop custom HMM targets. Hindawi Publishing Corporation 2003-04 /pmc/articles/PMC2447419/ /pubmed/18629132 http://dx.doi.org/10.1002/cfg.280 Text en Copyright © 2003 Hindawi Publishing Corporation. http://creativecommons.org/licenses/by/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Gollery, Martin Specialized Hidden Markov Model Databases for Microbial Genomics |
title | Specialized Hidden Markov Model Databases for Microbial Genomics |
title_full | Specialized Hidden Markov Model Databases for Microbial Genomics |
title_fullStr | Specialized Hidden Markov Model Databases for Microbial Genomics |
title_full_unstemmed | Specialized Hidden Markov Model Databases for Microbial Genomics |
title_short | Specialized Hidden Markov Model Databases for Microbial Genomics |
title_sort | specialized hidden markov model databases for microbial genomics |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2447419/ https://www.ncbi.nlm.nih.gov/pubmed/18629132 http://dx.doi.org/10.1002/cfg.280 |
work_keys_str_mv | AT gollerymartin specializedhiddenmarkovmodeldatabasesformicrobialgenomics |