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» Predicting Nucleolar Proteins Using Support-Vector Machines
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BMCBI
2010
117views more  BMCBI 2010»
13 years 8 months ago
Identification of NAD interacting residues in proteins
Background: Small molecular cofactors or ligands play a crucial role in the proper functioning of cells. Accurate annotation of their target proteins and binding sites is required...
Hifzur Rahman Ansari, Gajendra P. S. Raghava
BMCBI
2006
180views more  BMCBI 2006»
13 years 8 months ago
Building multiclass classifiers for remote homology detection and fold recognition
Motivation Protein remote homology prediction and fold recognition are central problems in computational biology. Supervised learning algorithms based on support vector machines a...
Huzefa Rangwala, George Karypis
BMCBI
2008
228views more  BMCBI 2008»
13 years 8 months ago
Adaptive diffusion kernel learning from biological networks for protein function prediction
Background: Machine-learning tools have gained considerable attention during the last few years for analyzing biological networks for protein function prediction. Kernel methods a...
Liang Sun, Shuiwang Ji, Jieping Ye
BMCBI
2007
107views more  BMCBI 2007»
13 years 8 months ago
Prediction of potential drug targets based on simple sequence properties
Background: During the past decades, research and development in drug discovery have attracted much attention and efforts. However, only 324 drug targets are known for clinical dr...
Qingliang Li, Luhua Lai
BMCBI
2007
130views more  BMCBI 2007»
13 years 8 months ago
Exploiting residue-level and profile-level interface propensities for usage in binding sites prediction of proteins
Background: Recognition of binding sites in proteins is a direct computational approach to the characterization of proteins in terms of biological and biochemical function. Residu...
Qiwen Dong, Xiaolong Wang, Lei Lin, Yi Guan