Large-scale Protein-Protein Interaction prediction using novel kernel methods.
Knowledge of Protein-Protein Interactions (PPIs) can give us new insights into molecular mechanisms and properties of the cell. In this paper, we propose a novel domain-based kernel method to predict PPIs. A new kernel that measures the similarity between protein pairs based on a new feature representation is developed and applied to a large scale PPI database. Experimental results demonstrate its effectiveness. Furthermore, we evaluate the problem of cross-species PPI prediction and the effect of the number of negative samples on the performance of PPI predictions, which are two fundamental problems in most in silico PPI methods.
Chen
Xue-Wen
XW
Electrical Engineering and Computer Science Department, The University of Kansas, Lawrence, KS 66045, USA. xwchen@ku.edu
Han
Bing
B
Fang
Jianwen
J
Haasl
Ryan J
RJ