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ClusCo: clustering and comparison of protein models

BACKGROUND: The development, optimization and validation of protein modeling methods require efficient tools for structural comparison. Frequently, a large number of models need to be compared with the target native structure. The main reason for the development of Clusco software was to create a hi...

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Detalles Bibliográficos
Autores principales: Jamroz, Michal, Kolinski, Andrzej
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3645956/
https://www.ncbi.nlm.nih.gov/pubmed/23433004
http://dx.doi.org/10.1186/1471-2105-14-62
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author Jamroz, Michal
Kolinski, Andrzej
author_facet Jamroz, Michal
Kolinski, Andrzej
author_sort Jamroz, Michal
collection PubMed
description BACKGROUND: The development, optimization and validation of protein modeling methods require efficient tools for structural comparison. Frequently, a large number of models need to be compared with the target native structure. The main reason for the development of Clusco software was to create a high-throughput tool for all-versus-all comparison, because calculating similarity matrix is the one of the bottlenecks in the protein modeling pipeline. RESULTS: Clusco is fast and easy-to-use software for high-throughput comparison of protein models with different similarity measures (cRMSD, dRMSD, GDT_TS, TM-Score, MaxSub, Contact Map Overlap) and clustering of the comparison results with standard methods: K-means Clustering or Hierarchical Agglomerative Clustering. CONCLUSIONS: The application was highly optimized and written in C/C++, including the code for parallel execution on CPU and GPU, which resulted in a significant speedup over similar clustering and scoring computation programs.
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spelling pubmed-36459562013-05-09 ClusCo: clustering and comparison of protein models Jamroz, Michal Kolinski, Andrzej BMC Bioinformatics Software BACKGROUND: The development, optimization and validation of protein modeling methods require efficient tools for structural comparison. Frequently, a large number of models need to be compared with the target native structure. The main reason for the development of Clusco software was to create a high-throughput tool for all-versus-all comparison, because calculating similarity matrix is the one of the bottlenecks in the protein modeling pipeline. RESULTS: Clusco is fast and easy-to-use software for high-throughput comparison of protein models with different similarity measures (cRMSD, dRMSD, GDT_TS, TM-Score, MaxSub, Contact Map Overlap) and clustering of the comparison results with standard methods: K-means Clustering or Hierarchical Agglomerative Clustering. CONCLUSIONS: The application was highly optimized and written in C/C++, including the code for parallel execution on CPU and GPU, which resulted in a significant speedup over similar clustering and scoring computation programs. BioMed Central 2013-02-22 /pmc/articles/PMC3645956/ /pubmed/23433004 http://dx.doi.org/10.1186/1471-2105-14-62 Text en Copyright © 2013 Jamroz and Kolinski; 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.
spellingShingle Software
Jamroz, Michal
Kolinski, Andrzej
ClusCo: clustering and comparison of protein models
title ClusCo: clustering and comparison of protein models
title_full ClusCo: clustering and comparison of protein models
title_fullStr ClusCo: clustering and comparison of protein models
title_full_unstemmed ClusCo: clustering and comparison of protein models
title_short ClusCo: clustering and comparison of protein models
title_sort clusco: clustering and comparison of protein models
topic Software
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3645956/
https://www.ncbi.nlm.nih.gov/pubmed/23433004
http://dx.doi.org/10.1186/1471-2105-14-62
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