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PPSampler2: Predicting protein complexes more accurately and efficiently by sampling

The problem of predicting sets of components of heteromeric protein complexes is a challenging problem in Systems Biology. There have been many tools proposed to predict those complexes. Among them, PPSampler, a protein complex prediction algorithm based on the Metropolis-Hastings algorithm, is repo...

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Detalles Bibliográficos
Autores principales: Widita, Chasanah Kusumastuti, Maruyama, Osamu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4029527/
https://www.ncbi.nlm.nih.gov/pubmed/24565288
http://dx.doi.org/10.1186/1752-0509-7-S6-S14
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author Widita, Chasanah Kusumastuti
Maruyama, Osamu
author_facet Widita, Chasanah Kusumastuti
Maruyama, Osamu
author_sort Widita, Chasanah Kusumastuti
collection PubMed
description The problem of predicting sets of components of heteromeric protein complexes is a challenging problem in Systems Biology. There have been many tools proposed to predict those complexes. Among them, PPSampler, a protein complex prediction algorithm based on the Metropolis-Hastings algorithm, is reported to outperform other tools. In this work, we improve PPSampler by refining scoring functions and a proposal distribution used inside the algorithm so that predicted clusters are more accurate as well as the resulting algorithm runs faster. The new version is called PPSampler2. In computational experiments, PPSampler2 is shown to outperform other tools including PPSampler. The F-measure score of PPSampler2 is 0.67, which is at least 26% higher than those of the other tools. In addition, about 82% of the predicted clusters that are unmatched with any known complexes are statistically significant on the biological process aspect of Gene Ontology. Furthermore, the running time is reduced to twenty minutes, which is 1/24 of that of PPSampler.
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spelling pubmed-40295272014-06-06 PPSampler2: Predicting protein complexes more accurately and efficiently by sampling Widita, Chasanah Kusumastuti Maruyama, Osamu BMC Syst Biol Research The problem of predicting sets of components of heteromeric protein complexes is a challenging problem in Systems Biology. There have been many tools proposed to predict those complexes. Among them, PPSampler, a protein complex prediction algorithm based on the Metropolis-Hastings algorithm, is reported to outperform other tools. In this work, we improve PPSampler by refining scoring functions and a proposal distribution used inside the algorithm so that predicted clusters are more accurate as well as the resulting algorithm runs faster. The new version is called PPSampler2. In computational experiments, PPSampler2 is shown to outperform other tools including PPSampler. The F-measure score of PPSampler2 is 0.67, which is at least 26% higher than those of the other tools. In addition, about 82% of the predicted clusters that are unmatched with any known complexes are statistically significant on the biological process aspect of Gene Ontology. Furthermore, the running time is reduced to twenty minutes, which is 1/24 of that of PPSampler. BioMed Central 2013-12-13 /pmc/articles/PMC4029527/ /pubmed/24565288 http://dx.doi.org/10.1186/1752-0509-7-S6-S14 Text en Copyright © 2013 Widita and Maruyama; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Widita, Chasanah Kusumastuti
Maruyama, Osamu
PPSampler2: Predicting protein complexes more accurately and efficiently by sampling
title PPSampler2: Predicting protein complexes more accurately and efficiently by sampling
title_full PPSampler2: Predicting protein complexes more accurately and efficiently by sampling
title_fullStr PPSampler2: Predicting protein complexes more accurately and efficiently by sampling
title_full_unstemmed PPSampler2: Predicting protein complexes more accurately and efficiently by sampling
title_short PPSampler2: Predicting protein complexes more accurately and efficiently by sampling
title_sort ppsampler2: predicting protein complexes more accurately and efficiently by sampling
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4029527/
https://www.ncbi.nlm.nih.gov/pubmed/24565288
http://dx.doi.org/10.1186/1752-0509-7-S6-S14
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