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» Predicting Nucleolar Proteins Using Support-Vector Machines
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BMCBI
2005
107views more  BMCBI 2005»
13 years 5 months ago
Protein subcellular localization prediction for Gram-negative bacteria using amino acid subalphabets and a combination of multip
Background: Predicting the subcellular localization of proteins is important for determining the function of proteins. Previous works focused on predicting protein localization in...
Jiren Wang, Wing-Kin Sung, Arun Krishnan, Kuo-Bin ...
BMCBI
2008
134views more  BMCBI 2008»
13 years 5 months ago
Prediction of protein-protein binding site by using core interface residue and support vector machine
Background: The prediction of protein-protein binding site can provide structural annotation to the protein interaction data from proteomics studies. This is very important for th...
Nan Li, Zhonghua Sun, Fan Jiang
BMCBI
2010
88views more  BMCBI 2010»
13 years 5 months ago
Proteome scanning to predict PDZ domain interactions using support vector machines
Background: PDZ domains mediate protein-protein interactions involved in important biological processes through the recognition of short linear motifs in their target proteins. Tw...
Shirley Hui, Gary D. Bader
BMCBI
2006
106views more  BMCBI 2006»
13 years 5 months ago
Prediction of the functional class of metal-binding proteins from sequence derived physicochemical properties by support vector
Metal-binding proteins play important roles in structural stability, signaling, regulation, transport, immune response, metabolism control, and metal homeostasis. Because of their...
H. H. Lin, L. Y. Han, H. L. Zhang, C. J. Zheng, B....