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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 |
Sumario: | 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. |
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