This article is part of the supplement: Selected articles from the IEEE International Conference on Bioinformatics and Biomedicine 2011: Proteome Science
Proceedings
Predicting synthetic lethal genetic interactions in Saccharomyces cerevisiae using short polypeptide clusters
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
Proteome Science 2012, 10(Suppl 1):S4 doi:10.1186/1477-5956-10-S1-S4
Published: 21 June 2012Abstract
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.
