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This article is part of the supplement: Selected articles from the IEEE International Conference on Bioinformatics and Biomedicine 2011: Proteome Science

Open Access Proceedings

Predicting synthetic lethal genetic interactions in Saccharomyces cerevisiae using short polypeptide clusters

Yuehua Zhang1, Bo Li1, Pradip K Srimani1, Xuewen Chen2 and Feng Luo1*

Author Affiliations

1 School of Computing, Clemson University, Clemson, SC 29634, USA

2 Electrical Engineering and Computer Science Department, University of Kansas, Lawrence, KS 66045-7621, USA

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Proteome Science 2012, 10(Suppl 1):S4  doi:10.1186/1477-5956-10-S1-S4

Published: 21 June 2012

Abstract

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.