Predicts subcellular localization of virus proteins. Virus-ECC-mPLoc is based on a multi-label learning approach that can uses single-plex and multi-plex proteins to exploit correlations between subcellular locations. It uses a hybrid of Gene Ontology (GO) and Dipeptide Composition (DC) feature extraction methods that can handle the multiplex proteins. The tool can be particularly useful in the area of bioinformatics and proteomics.
The MOE Key Laboratory of Embedded System and Service Computing, Department of Control Science and Engineering, Tongji University, Shanghai, China; Department of Chemistry, College of Science, Shanghai University, Shanghai, China
Virus-ECC-mPLoc funding source(s)
Supported by the Natural Science Foundation of China under the Grant No. 60873129 and 61005006, and the Open Projects Program of National Laboratory of Pattern Recognition in China.