This is a sequence-based hot spot residue predictor through physicochemical characteristics of amino acids.

Reference:

Peng Chen, Jinyan Li, Limsoon Wong, Jianhua Huang, and Xin Gao, Accurate prediction of hot spot residues through physicochemical characteristics of amino acid sequences, PROTEINS: Structure, Function, and Bioinformatics. 2013, 81(8):1351-62.

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LigandRFs is a random forest-based approach to predict protein-ligand binding sites.

Reference:

Peng Chen, Jianhua Huang, and Xin Gao, LigandRFs: predict ligand-binding sites from sequence information through random forests. BMC Bioinformatics, Accepted.

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Reference:

Peng Chen, Limsoon Wong, Jinyan Li, Outlier detection: a challenge to clean interface data in protein hetero-complexes and the application, IEEE Transactions on Computational Biology and Bioinformatics, 2012, 9(4):1155-65.

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Reference:

Peng Chen, Jinyan Li, Sequence-based identification of interface residues by an integrative profile combining hydrophobic and evolutionary information, BMC Bioinformatics, 2010,11:402.

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Reference:

Peng Chen, Chunmei Liu, Legand Burge, Jinyan Li, Mahmood Mohanmad, Bill Southerland, and Clay Gloster, DomSVR: Domain Boundary Prediction with Support Vector Regression from sequence information Alone, Amino Acids, 2010, 39(3), 713-726 .

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Reference:

Peng Chen, Jinyan Li, Prediction of Protein Long-Range Contacts Using an Ensemble of Genetic Algorithm Classifiers with Sequence Profile Centers, BMC Structural Biology, 2010, 10(Suppl 1):S2.

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