Predicts mycobacterial membrane proteins and their types. MycoMemSVM is an online server and a binomial distribution-based feature selection technique able to select over-represented tripeptides. In the development of this method, the binomial distribution was used to pick out the over-represented tripeptides and the support vector machine (SVM) was used to perform prediction. This server can be helpful for the vast majority of experimental scientists who focus on mycobacterium and antimicrobial drugs.
Key Laboratory for NeuroInformation of Ministry of Education, Center of Bioinformatics, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China; Department of Physics, Center for Genomics and Computational Biology, College of Sciences, Hebei United University, Tangshan, China
MycoMemSVM funding source(s)
Supported by the Fundamental Research Funds for the Central Universities (ZYGX2009J081), the Scientific Research Foundation of Sichuan Province (2009JY0013), the National Natural Science Foundation of China (61202256, 61100092), the Scientific Research Startup Foundation of North China Coal Medical University (No. 10101115) and the Foundation of Scientific and Technological Department of Hebei Province (No. 11275532).