Predicts protein localization. PLPD can detect the likelihood of specific localization for a protein by using the Density-induced Support Vector Data Description (D-SVDD). D-SVDD is extended for this algorithm to run the prediction of protein subcellular localization. It utilizes three measurements for the assessment and to refine the protein localization predictor. PLPD approach is complimentary to other method such as the nearest neighbor or the discriminate covariant method.
Department of BioSystems, KAIST, Daejeon, South Korea; Advanced Information Technology Research Center, KAIST, Daejeon, South Korea; School of Computer Science and Engineering, Chung-Ang University, Seoul, South Korea
PLPD funding source(s)
Supported by National Research Laboratory Grant (2005-01450) and the Korean Systems Biology Research Grant (2005-00343) from the Ministry of Science and Technology.