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Predicting synthetic lethal genetic interactions in Saccharomyces cerevisiae using short polypeptide clusters
BACKGROUND: Protein synthetic lethal genetic interactions are useful to define functional relationships between proteins and pathways. However, the molecular mechanism of synthetic lethal genetic interactions remains unclear. RESULTS: In this study we used the clusters of short polypeptide sequences...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3380729/ https://www.ncbi.nlm.nih.gov/pubmed/22759581 http://dx.doi.org/10.1186/1477-5956-10-S1-S4 |
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author | Zhang, Yuehua Li, Bo Srimani, Pradip K Chen, Xuewen Luo, Feng |
author_facet | Zhang, Yuehua Li, Bo Srimani, Pradip K Chen, Xuewen Luo, Feng |
author_sort | Zhang, Yuehua |
collection | PubMed |
description | BACKGROUND: Protein synthetic lethal genetic interactions are useful to define functional relationships between proteins and pathways. However, the molecular mechanism of synthetic lethal genetic interactions remains unclear. RESULTS: In this study we used the clusters of short polypeptide sequences, which are typically shorter than the classically defined protein domains, to characterize the functionalities of proteins. We developed a framework to identify significant short polypeptide clusters from yeast protein sequences, and then used these short polypeptide clusters as features to predict yeast synthetic lethal genetic interactions. The short polypeptide clusters based approach provides much higher coverage for predicting yeast synthetic lethal genetic interactions. Evaluation using experimental data sets showed that the short polypeptide clusters based approach is superior to the previous protein domain based one. CONCLUSION: We were able to achieve higher performance in yeast synthetic lethal genetic interactions prediction using short polypeptide clusters as features. Our study suggests that the short polypeptide cluster may help better understand the functionalities of proteins. |
format | Online Article Text |
id | pubmed-3380729 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-33807292012-06-25 Predicting synthetic lethal genetic interactions in Saccharomyces cerevisiae using short polypeptide clusters Zhang, Yuehua Li, Bo Srimani, Pradip K Chen, Xuewen Luo, Feng Proteome Sci Proceedings BACKGROUND: Protein synthetic lethal genetic interactions are useful to define functional relationships between proteins and pathways. However, the molecular mechanism of synthetic lethal genetic interactions remains unclear. RESULTS: In this study we used the clusters of short polypeptide sequences, which are typically shorter than the classically defined protein domains, to characterize the functionalities of proteins. We developed a framework to identify significant short polypeptide clusters from yeast protein sequences, and then used these short polypeptide clusters as features to predict yeast synthetic lethal genetic interactions. The short polypeptide clusters based approach provides much higher coverage for predicting yeast synthetic lethal genetic interactions. Evaluation using experimental data sets showed that the short polypeptide clusters based approach is superior to the previous protein domain based one. CONCLUSION: We were able to achieve higher performance in yeast synthetic lethal genetic interactions prediction using short polypeptide clusters as features. Our study suggests that the short polypeptide cluster may help better understand the functionalities of proteins. BioMed Central 2012-06-21 /pmc/articles/PMC3380729/ /pubmed/22759581 http://dx.doi.org/10.1186/1477-5956-10-S1-S4 Text en Copyright ©2012 Zhang et al.; 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 | Proceedings Zhang, Yuehua Li, Bo Srimani, Pradip K Chen, Xuewen Luo, Feng Predicting synthetic lethal genetic interactions in Saccharomyces cerevisiae using short polypeptide clusters |
title | Predicting synthetic lethal genetic interactions in Saccharomyces cerevisiae using short polypeptide clusters |
title_full | Predicting synthetic lethal genetic interactions in Saccharomyces cerevisiae using short polypeptide clusters |
title_fullStr | Predicting synthetic lethal genetic interactions in Saccharomyces cerevisiae using short polypeptide clusters |
title_full_unstemmed | Predicting synthetic lethal genetic interactions in Saccharomyces cerevisiae using short polypeptide clusters |
title_short | Predicting synthetic lethal genetic interactions in Saccharomyces cerevisiae using short polypeptide clusters |
title_sort | predicting synthetic lethal genetic interactions in saccharomyces cerevisiae using short polypeptide clusters |
topic | Proceedings |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3380729/ https://www.ncbi.nlm.nih.gov/pubmed/22759581 http://dx.doi.org/10.1186/1477-5956-10-S1-S4 |
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