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Modern Computational Techniques for the HMMER Sequence Analysis

This paper focuses on the latest research and critical reviews on modern computing architectures, software and hardware accelerated algorithms for bioinformatics data analysis with an emphasis on one of the most important sequence analysis applications—hidden Markov models (HMM). We show the detaile...

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Detalles Bibliográficos
Autores principales: Meng, Xiandong, Ji, Yanqing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4393056/
https://www.ncbi.nlm.nih.gov/pubmed/25937944
http://dx.doi.org/10.1155/2013/252183
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author Meng, Xiandong
Ji, Yanqing
author_facet Meng, Xiandong
Ji, Yanqing
author_sort Meng, Xiandong
collection PubMed
description This paper focuses on the latest research and critical reviews on modern computing architectures, software and hardware accelerated algorithms for bioinformatics data analysis with an emphasis on one of the most important sequence analysis applications—hidden Markov models (HMM). We show the detailed performance comparison of sequence analysis tools on various computing platforms recently developed in the bioinformatics society. The characteristics of the sequence analysis, such as data and compute-intensive natures, make it very attractive to optimize and parallelize by using both traditional software approach and innovated hardware acceleration technologies.
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spelling pubmed-43930562015-05-03 Modern Computational Techniques for the HMMER Sequence Analysis Meng, Xiandong Ji, Yanqing ISRN Bioinform Review Article This paper focuses on the latest research and critical reviews on modern computing architectures, software and hardware accelerated algorithms for bioinformatics data analysis with an emphasis on one of the most important sequence analysis applications—hidden Markov models (HMM). We show the detailed performance comparison of sequence analysis tools on various computing platforms recently developed in the bioinformatics society. The characteristics of the sequence analysis, such as data and compute-intensive natures, make it very attractive to optimize and parallelize by using both traditional software approach and innovated hardware acceleration technologies. Hindawi Publishing Corporation 2013-09-03 /pmc/articles/PMC4393056/ /pubmed/25937944 http://dx.doi.org/10.1155/2013/252183 Text en Copyright © 2013 X. Meng and Y. Ji. https://creativecommons.org/licenses/by/3.0/ 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 Review Article
Meng, Xiandong
Ji, Yanqing
Modern Computational Techniques for the HMMER Sequence Analysis
title Modern Computational Techniques for the HMMER Sequence Analysis
title_full Modern Computational Techniques for the HMMER Sequence Analysis
title_fullStr Modern Computational Techniques for the HMMER Sequence Analysis
title_full_unstemmed Modern Computational Techniques for the HMMER Sequence Analysis
title_short Modern Computational Techniques for the HMMER Sequence Analysis
title_sort modern computational techniques for the hmmer sequence analysis
topic Review Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4393056/
https://www.ncbi.nlm.nih.gov/pubmed/25937944
http://dx.doi.org/10.1155/2013/252183
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