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» A New Machine Learning Approach for Protein Phosphorylation ...
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BMCBI
2010
103views more  BMCBI 2010»
13 years 6 months ago
PostMod: sequence based prediction of kinase-specific phosphorylation sites with indirect relationship
Background: Post-translational modifications (PTMs) have a key role in regulating cell functions. Consequently, identification of PTM sites has a significant impact on understandi...
Inkyung Jung, Akihisa Matsuyama, Minoru Yoshida, D...
BMCBI
2011
13 years 1 months ago
DoBo: Protein domain boundary prediction by integrating evolutionary signals and machine learning
Background: Accurate identification of protein domain boundaries is useful for protein structure determination and prediction. However, predicting protein domain boundaries from a...
Jesse Eickholt, Xin Deng, Jianlin Cheng
BMCBI
2006
95views more  BMCBI 2006»
13 years 6 months ago
Predicting DNA-binding sites of proteins from amino acid sequence
Background: Understanding the molecular details of protein-DNA interactions is critical for deciphering the mechanisms of gene regulation. We present a machine learning approach f...
Changhui Yan, Michael Terribilini, Feihong Wu, Rob...
BMCBI
2007
126views more  BMCBI 2007»
13 years 6 months ago
High-throughput identification of interacting protein-protein binding sites
Background: With the advent of increasing sequence and structural data, a number of methods have been proposed to locate putative protein binding sites from protein surfaces. Ther...
Jo-Lan Chung, Wei Wang, Philip E. Bourne
BMCBI
2007
91views more  BMCBI 2007»
13 years 6 months ago
A machine learning approach for the identification of odorant binding proteins from sequence-derived properties
Background: Odorant binding proteins (OBPs) are believed to shuttle odorants from the environment to the underlying odorant receptors, for which they could potentially serve as od...
Ganesan Pugalenthi, E. Ke Tang, Ponnuthurai N. Sug...