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National University of Singapore, Science Faculty, Computational Sci Dept
 
   
   

LIST OF PUBLICATIONS

Publications in the Area of Computational Biology and Drug Design

 

  1. Comparative analysis of machine learning methods in ligand-based virtual screening of large compound libraries. X.H. Ma, J. Jia, F. Zhu, Y. Xue, Z.R. Li and Y. Z. Chen.Comb. Chem. High Throughput Screen. 2008 (accepted).
  2. Simulation of DNA Electrophoresis in Systems of Large Number of Solvent Particles by Coarse-Grained Hybrid Molecular Dynamics Approach. R. Wang, J.S. Wang, G.R. Liu, J.Y. Han, N.G. Hadjiconstantinou and Y. Z. Chen.J Comput Chem. 2008 (accepted).
  3. Mechanisms of drug combinations from interaction and network perspectives J. Jia, F. Zhu, X.H. Ma, Z.W. Cao, Y.X. Li and Y.Z. Chen. Nat. Rev. Drug Discov., 2008 (accepted).
  4. Simulation of the Regulation of EGFR Endocytosis and EGFR-ERK Signaling by Endophilin-Mediated RhoA-EGFR Crosstalk. C.Y. Ung, H. Li, X.H. Ma, J. Jia, B.W. Li, B.C. Low and Y.Z. Chen.FEBS Lett. 582:2283-2290 (2008).Pubmed
  5. Evaluation of Virtual Screening Performance of Support Vector Machines Trained by Sparsely Distributed Active Compounds. X.H. Ma, R. Wang, S.Y. Yang, Z.R. Li, Y. Xue, Y.Q. Wei, B.C. Low and Y. Z. Chen.J Chem Inf Model. 48(6):1227-1237 (2008) (accepted).
  6. Prediction of Antibiotic Resistance Proteins from Sequence Derived Properties Irrespective of Sequence Similarity. H.L. Zhang, H.H. Lin, L. Tao, X.H. Ma, J.L. Dai, J.Jia, Z.W. Cao.Int J Antimicrob Agents. 2008 (accepted).
  7. Advances in Machine Learning Prediction of Toxicological Properties and Adverse Drug Reactions of Pharmaceutical Agents. X.H. Ma, R. Wang, Y. Xue, Z.R. Li, S.Y. Yang, Y.Q. Wei and Y.Z. Chen.Current Drug Safety. 3(2):100-114 (2008).
  8. Homology-Free Prediction of Functional Class of Proteins and Peptides by Support Vector Machines. F. Zhu, L.Y. Han, X. Chen, H.H. Lin, S. Ong, B. Xie, H.L. Zhang, Y.Z. Chen. Current Protein and Peptide Science. 9:70-95 (2008).
  9. Learning the drug target-likeness of a protein H. Xu, H.Y. Xu, M. Lin, W. Wang, Z.M. Li, J.J. Huang, Y.Z Chen, X. Chen.Proteomics. 7(23):4255-4263 (2007).Pubmed
  10. A support vector machines approach for virtual screening of active compounds of single and multiple mechanisms from large libraries at an improved hit-rate and enrichment factor. L.Y. Han, X.H. Ma, H.H. Lin, J. Jia, F. Zhu, Y. Xue, Z.R. Li, Z.W. Cao, Z.L. Ji, Y.Z. Chen. J. Mol. Graph. Mod. 26(8):1276-1286 (2007) Pubmed
  11. Efficacy of different protein descriptors in predicting protein functional families. S. Ong, H.H. Lin, Y.Z. Chen, Z.R. Li, Z.W. Cao. BMC Bioinforamtics. 8:300 (2007).Pubmed
  12. DITOP: drug-induced toxicity related protein database. J.X Zhang, W.J. Huang, J.H. Zeng, W.H. Huang, Y. Wang, R. Zhao, B.C. Han, Q.F. Liu, Y.Z. Chen, Z.L. Ji. Bioinforamtics. 23(13):1710-1712 (2007).Pubmed
  13. Formulation Development of Transdermal Dosage Forms: Quantitative Structure-Activity Relationship Model for Predicting Activities of Terpenes that Enhance Drug Penetration Through Human Skin . L. Kang, C.W. Yap, P.F. Lim, Y.Z. Chen,P.C. Ho, Y.W. Chan, G.P. Wang, S.Y. Chan. J Control Release. 120(3):211-219 (2007).Pubmed
  14. Trends in the Exploration of Therapeutic Targets for the Treatment of Endocrine, Metabolic and Immune Disorders. X. Chen, C.J. Zheng, L.Y. Han, B. Xie and Y.Z. Chen. Endocr Metab Immune Disord Drug Targets 7(3):225-231 (2007).Pubmed
  15. Prediction of Functional Class of Proteins and Peptides Irrespective of Sequence Homology by Support Vector Machines. Z.Q. Tang, H.H. Lin, H.L. Zhang, L.Y. Han, X. Chen, Y.Z. Chen. Bioinformatics Biol. Insights 1:19-47 (2007).
  16. Derivation of Stable Microarray Cancer-differentiating Signatures by a Feature-selection Method Incorporating Consensus Scoring of Multiple Random Sampling and Gene-Ranking Consistency Evaluation. Z.Q. Tang, L.Y. Han, H.H. Lin, J. Cui, J. Jia, B.C. Low, B.W. Li, Y.Z. Chen. Cancer Res. 67(20):9996-10003 (2007).Pubmed
  17. Regression Methods for Developing QSAR and QSPR Models to Predict Compounds of Specific Pharmacodynamic, Pharmacokinetic and Toxicological Properties. C. W. Yap, H. Li, Z. L. Ji and Y. Z. Chen. Mini. Rev. Med. Chem. 7(11):1097-1107 (2007). Pubmed
  18. Prediction of Factor Xa Inhibitors by Machine Learning Methods. H.H Lin, L.Y. Han, C.W. Yap, Y. Xue, X.H. Liu, F. Zhu, and Y.Z Chen. J. Mol. Graph. Mod. 26(2):505-518 (2007) Pubmed
  19. AAIR: Antibody Antigen Information Resource. Z.Q.Tang, L.Y. Han, B. Xie, C.Y. Ung, L. Jiang, Z.W. Cao, and Y.Z Chen. J Immunol 178(8): 4705 (2007).Pubmed
  20. Support vector machines approach for predicting druggable proteins: recent progress in its exploration and investigation of its usefulness. L.Y. Han, C.J. Zheng, B. Xie, J. Jia, X.H. Ma, F. Zhu, H.H. Lin, X. Chen, and Y.Z. Chen. Drug Discov. Today 12(7-8): 304-313 ( 2007).Pubmed
  21. Advances in exploration of machine learning methods for predicting functional class and interaction profiles of proteins and peptides irrespective of sequence homology J. Cui, L.Y. Han, H.H. Lin, Z.Q. Tang, Z.L. Ji, Z.W. Cao, Y.X. Li, and Y.Z. Chen. Curr. Bioinformatics 2(2): 95-112 (2007).
  22. Machine Learning Approaches for Predicting Compounds That Interact with Therapeutic and ADMET Related Proteins. H. Li, C.W. Yap, C.Y. Ung, Y. Xue, Z.R. Li, L.Y. Han, H.H. Lin and Y.Z. Chen. J. Pharm. Sci. 96(11):2838-2860 (2007).Pubmed
  23. Are Herb-Pairs of Traditional Chinese Medicine Distinguishable from Others? Pattern Analysis and Artificial Intelligence Classification Study of Traditionally-Defined Herbal Properties. C.Y. Ung, H. Li, Z.W. Cao, Y.X. Li and Y.Z. Chen. J. Ethnopharmacol. 111(2):371-377 (2007).Pubmed
  24. MODEL -- Molecular Descriptor Lab: A Web-Based Server for Computing Structural and Physicochemical Features of Compounds. Z.R. Li, L. Y. Han, Y. Xue, C. W. Yap, H. Li, L. Jiang, and Y. Z. Chen. Biotechnol. Bioeng 97(2):389-96 (2007).Pubmed
  25. Computer Prediction of Cardiovascular and Hematological Agents by Statistical Learning Methods X. Chen, H. Li, C.W. Yap, C.Y. Ung, L. Jiang, Z.W. Cao, Y.X. Li and Y.Z. Chen Cardiovasc. Hematol. Agents Med. Chem. 5(1):11-19 ( 2007).Pubmed
  26. In Silico Prediction of Pregnane X Receptor Activators by Machine Learning Approaches. C.Y. Ung, H. Li, C.W. Yap and Y.Z. Chen. Mol. Pharmacol. 71(1):158-168 (2007).Pubmed
  27. PharmGED: Pharmacogenetic Effect Database B. Xie, C.J. Zheng, L. Y. Han, S. Ong, J. Cui, H.L. Zhang, L. Jiang, X. Chen and Y. Z. Chen. Clin. Pharmacol. Ther. 81(1): 29 (2007).Pubmed
  28. Prediction of MHC-Binding Peptides of Flexible Lengths from Sequence-Derived Structural and Physicochemical Properties J. Cui, L.Y. Han, H.H. Lin, H.L. Zhang, Z.Q. Tang, C.J. Zheng, Z.W. Cao, and Y.Z. Chen . Mol. Immunol. 44: 866-877 (2007).Pubmed
  29. Computer Prediction of Allergen Proteins from Sequence-Derived Protein Structural and Physicochemical Properties J. Cui, L.Y. Han, H.H. Lin, Z.Q. Tang, C.J. Zheng, Z.W. Cao, and Y.Z. Chen . Mol. Immunol. 44(4): 514-520 (2007).Pubmed
  30. PharmGED: Pharmacogenetic Effect Database. C.J.Zheng, L.Y.Han, B.Xie, C.Y.Liew, S.Ong, J.Cui, H.L.Zhang, Z.Q.Tang, S.H.Gan, L.Jiang and Y.Z. Chen. Nucleic Acids Res. 35:D794-D799 Sp. Iss. SI (2007)>.Pubmed
  31. Database of traditional Chinese medicine and its application to studies of mechanism and to prescription validation. X Chen, H Zhou, YB Liu, JF Wang, H Li, CY Ung, LY Han, ZW, Cao and YZ Chen Br. J. Pharmacol. 149(8):1092-1103 (2006).Pubmed
  32. Prediction of the Functional Class of Metal-Binding Proteins from Sequence Derived Physicochemical Properties by Support Vector Machine Approach. H.H. Lin, L.Y. Han, H.L. Zhang, C.J. Zheng, B. Xie, and Y.Z. Chen. BMC Bioinformatics 7(Suppl 5): S13 (2006).Pubmed
  33. Classification of a Diverse Set of Tetrahymena Pyriformis Toxicity Chemical Compounds from Molecular Descriptors by Statistical Learning Methods Y. Xue, H. Li, C.Y. Ung, C.W. Yap and Y.Z. Chen Chem. Res. Toxicol. 19 (8): 1030-1039 (2006). Pubmed
  34. Usefulness of Traditionally-Defined Herbal Properties for Distinguishing Prescriptions of Traditional Chinese Medicine from Non-Prescription Recipes C.Y. Ung, H. Li, C.Y. Kong, J.F. Wang and Y.Z. Chen. J. Ethnopharmacol. 109 (1): 21-28 (2006). Pubmed
  35. Tannic acid, a potent inhibitor of epidermal growth factor receptor tyrosine kinase Bin Yang E, Wei L, Zhang K, Chen YZ, Chen WN . J Biochem (Tokyo) 139(3):495-502 (2006). Pubmed
  36. Military vehicle classification via acoustic and seismic signals using statistical learning methods Xiao HG, Cai CZ, Chen YZ. Inter. J. Mod. Phys. C 17 (2): 197-212 FEB (2006).
  37. PROFEAT: A Web Server for Computing Structural and Physicochemical Features of Proteins and Peptides from Amino Acid Sequence. Z.R. Li, H.H. Lin, L.Y. Han, L. Jiang, X. Chen, and Y.Z. Chen. Nucleic Acids Res.Jul 1;34(Web Server issue):W32-7 (2006).Pubmed
  38. Recent progresses in the application of machine learning approach for predicting protein functional class independent of sequence similarity. L.Y. Han, J. Cui, H.H. Lin, Z.L. Ji, Z.W. Cao, Y.S. Li, and Y.Z. Chen Proteomics. Vol.6: 4023-4037 (2006).Pubmed
  39. MHC-BPS: MHC-Binder Prediction Server for Identifying Peptides of Flexible Lengths from Sequence-Derived Physicochemical Properties. J. Cui, L.Y. Han, H.H. Lin, Z.Q. Tang, C.J. Zheng, Z.W. Cao, and Y.Z. Chen Immunogenetics 58(8):607-13 (2006) . Pubmed
  40. Application of Support Vector Machines to in silico Prediction of Cytochrome P450 Enzyme Substrates and Inhibitors. C. W. Yap, Y. Xue, Z. R. Li, and Y. Z. Chen Curr. Top. Med. Chem. 6(15):1593-1607 (2006).Pubmed
  41. Prediction of Estrogen Receptor Agonists and Characterization of Associated Molecular Descriptors by Statistical Learning Methods. H. Li, C. Y. Ung, C. W. Yap, Y. Xue, Z. R. Li and Y. Z. Chen. J. Mol. Graph. Mod. 25 (3): 313-323 (2006).Pubmed
  42. In silico Search of Putative Adverse Drug Reaction Related Proteins as a Potential Tool for Facilitating Drug Adverse Effect Prediction. Z. L. Ji, Y. Wang, L. Yu, L. Y. Han, C. J. Zheng, and Y. Z. Chen. Toxicol Lett. 164:104-112 (2006). Pubmed
  43. Information of ADME-associated proteins and potential application for pharmacogenetic prediction of drug responses.C.J. Zheng, L.Y. Han, X. Chen, Z.W. Cao, J. Cui, H.H. Lin, H.L. Zhang, H. Li and Y. Z. Chen. Curr. Pharmacogenomics. 4(2):87-103 (2006).
  44. Therapeutic Targets: Progress of Their Exploration and Investigation of Their Characteristics. C.J. Zheng, L.Y. Han, C. W. Yap, Z. L. Ji, Z. W. Cao and Y. Z. Chen. Pharmacol. Rev. 58:259-279(2006)Pubmed.
  45. Increasing the Odds of Drug Hit Identification by Screening Against Receptor Homologs? Z.L. Ji, Z.R. Li, J.F. Wang, C.Z. Cai, L.Y. Han, C.J. Zheng, and Y.Z. Chen. Lett. Drug. Des. Discov. 3(3):200-204 (2006)
  46. Progress and Difficulties in the Exploration of Therapeutic Targets C.J. Zheng, L.Y. Han, C. W. Yap, B. Xie, and Y. Z. Chen Drug Discov. Today 11(9-10):412-420 (2006)Pubmed
  47. Prediction of Compounds with Specific Pharmacodynamic, Pharmacokinetic or Toxicological Property by Statistical Learning Methods. C. W. Yap, Y. Xue, H. Li, Z. R. Li, C. Y. Ung, L. Y. Han, C. J. Zheng, Z. W. Cao and Y. Z. Chen. Mini. Rev. Med. Chem. 6:449-459 (2006)Pubmed
  48. Prediction of the Functional Class of Lipid-Binding Proteins from Sequence Derived Properties Irrespective of Sequence Similarity. H.H. Lin, L.Y. Han, H.L. Zhang, C.J. Zheng, B. Xie, and Y.Z. Chen. J. Lipid Res. 47(4):824-31 (2006)Pubmed
  49. PEARLS: Program for Energetic Analysis of Receptor-Ligand System. L.Y. Han, H.H. Lin, Z. R. Li, C.J. Zheng, Z.W. Cao, B. Xie, and Y. Z. Chen. J. Chem. Inf. Model. 23(1):445-450 (2006)Pubmed
  50. Traditional Chinese Medicine Information Database. Z. L. Ji, H. Zhou, J. F. Wang, L. Y. Han, C. J. Zheng, and Y. Z. Chen. J. Ethnopharmacol. 103(3):501 (2006).Pubmed
  51. Statistical learning approach for predicting specific pharmacodynamic, pharmacokinetic or toxicological properties of pharmaceutical agents. H. Li, C. W. Yap, Y. Xue, Z. R. Li, C. Y. Ung, L. Y. Han, and Y. Z. Chen Drug Dev. Res. 66:245-259(2006)
  52. Prediction of Transporter Family by Support Vector Machine Approach H. H. Lin, L.Y. Han, C.Z. Cai, Z. L. Ji, and Y.Z. Chen. Proteins. 62 (1): 218-31 (2006)Pubmed
  53. Quantitative structure-pharmacokinetic relationships for drug clearance by using statistical learning methods. C. W. Yap, Z. R. Li, and Y. Z. Chen. J. Mol. Graph. Mod 24 (5): 383-395 (2006).Pubmed
  54. Prediction of Putative Adverse Drug Reaction-Related Proteins from Primary Sequence by Support Vector Machines. Z. L. Ji, L. Y. Han, C. J. Zheng,Z.W. Cao and Y. Z. Chen. Int. J. of Pharm. Med. 19(5-6):317-322 (2005) .
  55. Prediction of Functional Class of Novel Bacterial Proteins without the Use of Sequence Similarity by a Statistical Learning Method.J. Cui, L. Y. Han, C. Z. Cai, C.J.Zheng, Z. L. Ji, and Y. Z. Chen.J. Mol. Microbiol. Biotech. 9 (2): 86-100 (2005)
  56. Prediction of Functional Class of the SARS Coronavirus Proteins by a Statistical Learning Method.C.Z. Cai, L.Y. Han,X.Chen,Z.W. Cao,Y.Z. Chen. J. Proteome Res. 4 (5): 1855-1862 (2005).
  57. Effect of Selection of Molecular Descriptors on the Prediction of Blood-Brain Barrier Penetrating and Non-penetrating Agents by Statistical Learning Methods. H. Li, C. W. Yap, C. Y. Ung,Y. Xue, Z. W. Cao, and Y. Z. Chen. J. Chem. Inf. Model. 45 (5): 1376-1384 (2005).
  58. Prediction of Functional Class of Novel Plant Proteins by a Statistical Learning Method. L. Y. Han, C. J. Zheng, H. H. Lin, J. Cui, H. Li, H. L. Zhang, Z. Q. Tang, and Y. Z. Chen, New Phytologist. 168:109-121(2005)
  59. Assessment of approximate string matching in a biomedical text retrieval problem . J.F. Wang, Z.R.Li,C.Z.Cai, and Y. Z. Chen.Comput. Biol. Med. 35(8): 717-724 (2005).
  60. TCM-ID: Traditional Chinese Medicine information database. J. F. Wang, H. Zhou, L. Y. Han, Z.W. Cao , X. Chen and Y. Z. Chen,Clin. Pharmacol. Ther.. 78(1):92-93 (2005).
  61. Prediction of Cytochrome P450 3A4, 2D6, 2C9 Inhibitors and Substrates by Using Support Vector Machines. C.W. Yap, Y.Z.Chen J. Chem. Inf. Model. 45(4): 982-992 (2005).
  62. Prediction of Genotoxicity of Chemical Compounds by Statistical Learning Methods. H. Li, C. Y. Ung, C. W. Yap, Y. Xue, Z. R. Li, Z. W. Cao, and Y. Z. Chen. Chem Res Toxicol.18(6):1071-1080 (2005).
  63. A Computer Method for Validating Traditional Chinese Medicine Herbal Prescriptions. J. F. Wang,C. Z. Cai, C. Y. Kong, Z. W. Cao and Y. Z. Chen. Am. J. Chin. Med.33(2):281-297(2005).
  64. Trends in Exploration of Therapeutic Targets C.J. Zheng, L.Y. Han, C. W. Yap, B. Xie, and Y. Z. Chen, Drug News Perpect. 18(2):109-127 (2005)
  65. Computer prediction of drug resistance mutations in proteins. Z. W. Cao, L. Y. Han, C. J. Zheng, Z. L. Ji, X. Chen, H. H. Lin and Y. Z. Chen Drug Discov. Today 10(7):521-529 (2005)
  66. Effect of training datasets on support vector machine prediction of protein-protein interactions S.L. Lo, C. Z. Cai, Y.Z. Chen and Maxey C. M. Chung.Proteomics. 5(4):876-884 (2005).
  67. Prediction of Functional Class of Novel Viral Proteins by a Statistical Learning Method Irrespective of Sequence Similarity. L.Y.Han, C.Z Cai, Z. L. Ji, Y.Z. Chen. Virology 331(1):136-143 (2005).
  68. Quantitative structure-pharmacokinetic relationships for drug distribution properties by using general regression neural network. C. W. Yap, Y.Z.Chen J Pharm Sci 94(1):153-168 (2005).
  69. Predicting Functional Family of Novel Enzymes Irrespective of Sequence Similarity: A Statistical Learning Approach. L.Y.Han, C.Z.Cai, Z.L.Ji, Z.W.Cao,J.Cui, Y.Z.Chen Nucleic Acids Res.32(21): 6437-6444(2004).
  70. Drug ADME-Associated Protein Database as a Resource for Facilitating Pharmacogenomics Research. C.J. Zheng, L. Z. Sun, L. Y. Han, Z. L. Ji, X. Chen, and Y. Z. Chen. Drug. Dev. Res. 62:134–142 (2004).
  71. Density Functional Theory Studies on Structure, Spectra, and Electronic Properties of 3,7-Dinitrodibenzobromolium Cation and Chloride.X. H., Y. P. Feng,Y. Z. Chen.J. Phys. Chem. A, 108:7596-7602 (2004).
  72. TRMP: A Database of Therapeutically Relevant Multiple-Pathways. C.J.Zheng, H. Zhou, B. Xie, L.Y. Han, C.W. Yap, and Y. Z. Chen, Bioinformatics. 20(14):2236-41(2004)
  73. Effect of molecular descriptor feature selection in support vector machine classification of pharmacokinetic and toxicological properties of chemical agents.Xue, Y.; Li, Z. R.; Yap, C. W.; Sun, L. Z.; Chen, X.; Chen, Y. Z. J.Chem. Inf. Comput. Sci. 44,1630-1638(2004)
  74. Prediction of p-glycoprotein substrates by support vector machine approach.Xue, Y.; Yap, C. W.; Sun, L. Z.; Cao, Z. W.; Wang, J. F.; Chen, Y. Z. J.Chem. Inf. Comput. Sci. 44(4), 1497-505 (2004)
  75. MoViES: Molecular Vibrations Evaluation Server for Analysis of Fluctuational Dynamics of Proteins and Nucleic Acids. Z.W. Cao, Y. Xue, L.Y. Han, B. Xie, H. Zhou, C.J. Zheng, H.H. Lin and Y. Z. Chen, Nucleic Acids Res.32(Web Server Issue),W679-W685. (2004).
  76. Prediction of torsade-causing potential of drugs by support vector machine approach.Yap, C. W., Cai, C. Z., Xue, Y., and Chen, Y. Z. Toxicol. Sci. 79(1),170-177. (2004).
  77. Enzyme Family Classification by Support Vector Machines.C.Z. Cai, L.Y. Han, Z.L. Ji, Y.Z. Chen .Proteins. 55,66-76 (2004).
  78. Prediction of RNA-Binding Proteins from Primary Sequence by Support Vector Machine Approach.L.Y. Han, C.Z. Cai, S. L. Lo, Maxey C. M. Chung,Y. Z. Chen. RNA. 10(3),355-368. (2004).
  79. Advances in modeling of biomolecular interactions.C.Z.Cai, Z.R. Li, W. L. Wang, Y.Z. Chen. Acta Pharmacol. Sin.25,1-8(2004).
  80. Support Vector Machine Classification of Physical and Biological Datasets.C.Z. Cai, W.L.Wang, and Y.Z.Chen. Inter.J.Mod.Phys.C 14(5),575 - 585. (2003).
  81. Protein function classification via support vector machine approach.C.Z. Cai ,W.L. Wang, L.Z. Sun, Y.Z. Chen. Math Biosci, 185, 111-122 (2003).
  82. Can an In-Silico Drug-Target Search Method be Used to Probe Potential Mechanisms of Medicinal Plant Ingredients? X. Chen, C. Y. Ung, and Y. Z. Chen. Nat. Prod. Rep., 20, 432 - 444 (2003).
  83. DART: Drug Adverse Reaction Target Database. Z. L. Ji, L. Y. Han, Chun Wei Yap, Li Zhi Sun, Xin Chen, and Yu Zong Chen .Drug Safety 26(10), 685-690 (2003).
  84. SVM-Prot: Web-Based Support Vector Machine Software for Functional Classification of a Protein from Its Primary Sequence.C.Z. Cai, L.Y. Han, Z.L. Ji, X. Chen, Y.Z. Chen. Nucleic Acids Res., 31(13),3692-3697. (2003).
  85. Calculation of Free Energy of the Integrable Landau-Lifshitz Model. C.Z. Cai, W.L. Wang, Y.Z. Chen. Chin. Phys. Lett., 20(7),1009-1012(2003).
  86. Internet Resources for Proteins Associated with Drug Therapeutic Effects, Adverse Reactions, and ADME. Z. L. Ji, L. Z. Sun, X. Chen, C. J. Zheng, L. X. Yao, L. Y. Han, Z.W. Cao, J. F. Wang, W. K. Yeo, C.Z. Cai, and Y. Z. Chen.Drug Discov. Today, 8(12),526-529. (2003).
  87. KDBI:Kinetic Data of Bio-molecular Interactions Database. Z. L. Ji, X. Chen, C. J. Zheng, L.X. Yao, L. Y. Han , W. K. Yeo, P. C. Chung, H. S. Puy, Y. T. Tay, A. Muhammad, and Y. Z. Chen. Nucleic. Acids. Res., 31(1), 255-257. (2003).
  88. Correlation between Normal Modes in The 20-200cm-1 Frequency Range and Localized Torsion Motions Related to Certain Collective Motions in Proteins. Z. W. Cao, X. Chen and Y. Z. Chen.J. Mol. Graph. Mod. 21,309-319. (2003).
  89. ADME-AP: A database of ADME associated proteins.L. Z. Sun, Z. L. Ji, X. Chen, J. F. Wang, and Y. Z. Chen. Bioinformatics., 18,1699-1700 . (2002).
  90. CLiBE: A Database of Computed Ligand Binding Energy for Ligand-Receptor Complexes and Its Potential Use in the Analysis of Drug Binding Competitiveness. X. Chen, Z. L. Ji, D.G. Zhi, and Y. Z. Chen, Comput. Biol. Chem. 26, 661-666. (2002).
  91. Computational Method for Drug Target Search and Application in Drug Discovery. Y. Z. Chen, Z. R. Li and C. Y. Ung, J. Theor. Comp. Chem., 1, 213-224. (2002).
  92. Absorption, distribution, metabolism, and excretion-associated protein database . L. Z. Sun, Z. L. Ji, X. Chen, J. F. Wang, and Y. Z. Chen,, Clin. Pharmacol. Ther. , 71, 405 (2002).
  93. Computer Automated Prediction of Putative Therapeutic and Toxicity Protein Targets of Bioactive Compounds from Chinese Medicinal Plants. Y. Z. Chen and C. Y. Ung, Am. J. Chin. Med., 30, 139-154. (2002).
  94. TTD: Therapeutic Target Database. X. Chen, Z.L. Ji, and Y. Z. Chen, Nucleic. Acids. Res., 30, 412-415 (2002).
  95. Inhibition of epidermal growth factor receptor (EGFR) tyrosine kinase by chalcone derivatives. E. B. Yang, Y. J. Guo, K Zhang, Y.Z. Chen, and P. Mack, BBA: Prot. Struct. Mol. Enzym.  1550, 144-152 (2001).
  96. Prediction of Potential Toxicity and Side Effect Protein Targets of a Small Molecule by a Ligand-Protein Inverse Docking Approach.Y. Z. Chen, C. Y. Ung, J. Mol. Graph. Mod., 20, 199-218 (2001).
  97. Can an optimization/scoring procedure in ligand-protein docking be employed to probe drug-resistant mutations in proteins? Y. Z. Chen, X. L. Gu, and Z. W. Cao, J. Mol. Graph. Mod. 19, 560-570 (2001).
  98. A computer approach for finding putative protein targets of a small molecule. Y. Z. Chen, FASEB J 15, A915 (2001).
  99. Application of computer-aided drug target search in probing molecular mechanism of bioactive Chinese natural products. Y. Z. Chen, and C. Y. Ung, Chin. J. Med. Chem. 11, 145-148 (2001).
  100. Ligand-Protein Inverse Docking and Its Potential Use in Computer Search of Putative Protein Targets of a Small Molecule. Y. Z. Chen and D. G. Zhi, Proteins, 43, 217-226 (2001).
  101. Hydrogen bond disruption probability in proteins by a modified selfconsistent harmonic approach. Z. W. Cao and Y. Z. Chen, Biopolymers, 58, 319-328 (2001).
  102. Computer search of putative protein targets of a small molecule. Y.Z. Chen, Biophys. J. 80, 497A (2001).
  103. Spontaneous base flipping in DNA and its possible role in methyltransferase binding.Y.Z. Chen, V. Mohan, and R. H. Griffey, Phys. Rev. E62, 1133-1137 (2000).
  104. Base Opening in RNA and DNA duplexes: Implication for RNA stability.Y.Z. Chen, V. Mohan, and R. H. Griffey, Phys. Rev. E61, 5640-5645 (2000).
  105. Modified self-consistent harmonic approach to thermal fluctuational disruption of disulfide bonds in proteins. Y.Z. Chen, Phys. Rev. E60, 5938-5942 (1999).
  106. Molecular basis for the stereospecificity of Candida rugosa Lipase (CRL) towards ibuprofen. B. S. Lakshmi, P. Kangueane, Y. Guo., Y. Z. Chen, and P. Gautam., Biocatal Biotransfor 17, 475-486 (1999).
  107. Principal Torsion Angles of Collective Motions in Biomolecules: A Study on Single Base Opening in DNA Duplexes. Y.Z. Chen, V. Mohan, and R.H. Griffey, Phys. Rev. E58, 909-913 (1998).
  108. Effect of backbone zeta torsion angle on low energy single base opening in B-DNA crystal structures. Y.Z. Chen, V. Mohan, and R.H. Griffey, Chem. Phys. Lett. 287, 570 (1998).
  109. Drug binding to DNA: Observation of the drug-DNA hydrogen-bond-stretching modes of netropsin bound to DNA via Raman spectroscopy. S.A. Lee, A. Rupprecht, and Y.Z. Chen, Phys. Rev. Lett. 80, 2241 (1998).
  110. The opening of a single base without perturbations of neighboring nucleotides: A study on crystal B-DNA duplex d(CGCGAATTCGCG)2. Y.Z. Chen, V. Mohan, and R.H. Griffey, J. Biomol. Struct. Dyn. 15, 765 (1998).
  111. Recent results on the statistical mechanis of intergrable models in 1+1 dimensions. Y.Z Chen, R. K. Bullough, D. J. Pilling and J. Timonon. World aquaculture. (1998)
  112. Theory of DNA melting based on the Peyrard-Bishop model. Y.L. Zhang, W.M. Zheng, J.X. Liu, Y.Z. Chen, Phys. Rev. E56, 7100-7115 (1997).
  113. A general random walk model of ATP-driven helicase translocation along DNA. Y.Z. Chen, Dong Mi, He-Shang Song, and Xian-Ju Wang, Phys. Rev. E56, 919 (1997).
  114. Effect of drug binding induced deformation on the vibrational spectrum of a daunomycin-DNA complex. Y. Z. Chen, J.W. Powell, S.A. Lee and E.W. Prohofsky, Phys. Rev. E55, 7414 (1997).
  115. Calculation of the binding affinity of the anticancer drug daunomycin to DNA by a statistical mechanics approach. Y.Z. Chen, and Yong-Li Zhang, Phys. Rev. E55, 7390 (1997).
  116. Binding stability of a cross-linked drug: Calculation of an anticancer drug cisplatin-DNA complex. Y.Z. Chen, E.W. Prohofsky, and Yong-Li Zhang, Phys. Rev. E55, 5843 (1997).
  117. Vibrational Analysis of Phosphrothioate DNA: II. The POS group in the model compound dimethyl phosphorothioate [CH_3O)_2(POS)]-. C.A. Steinke, K.K. Reeves, J.W. Powell, S.A. Lee, Y.Z. Chen, T. Wyrzykiewicz, R.H. Griffey, and V. Mohan. J. Biomol. Struct. Dyn. 14, 509 (1997).
  118. Vibrational normal modes and dynamical stability of DNA triplex Poly(dA)-2Poly(dT): S-type structure is more stable and in better agreement with observations in solution. Y.Z. Chen, J.W. Powell, and E.W. Prohofsky. Biophys. J.72, 1327 (1997).
  119. Sequence dependent DNA melting predicted by a microscopic statistical theory. Y. Z. Chen and E.W. Prohofsky, Eur. Biophys. J. 25, 9 (1996).
  120. Melting profile and temperature dependent binding constant of an anticancer drug daunomycin-DNA complex. Y.Z. Chen and E.W. Prohofsky, Eur. Biophys. J. 24, 203 (1996).
  121. Stability and conformation of [d(T)-d(A)-d(T)](n). Y.Z. Chen and E.W. Prohofsky, Biophys. J. 70, SUPM7 (1996).
  122. Calculation of the dynamics of drug binding in a netropsin-DNA complex. Y. Z. Chen and E.W. Prohofsky, Phys. Rev. E51, 5048 (1995).
  123. Normal mode calculation of a netropsin-DNA complex: Effect of structural deformation on vibrational spectrum. Y. Z. Chen and E.W. Prohofsky, Biopolymers 35, 657 (1995).
  124. Sequence and temperature dependence of the interbase hydrogen bond breathing modes in B-DNA polymers. Comparison with low frequency Raman peaks and their role in helix melting. Y. Z. Chen and E.W. Prohofsky, Biopolymers35, 573 (1995).
  125. Nonlinear effects and thermal expansion as expressed in selfconsistent phonon calculations on the temperature dependence of a phase change: Application to the B to Z conformation change in DNA. Y.Z. Chen and E.W. Prohofsky, Phys. Rev. E49, 3444 (1994).
  126. Premelting base pair opening probability and drug binding constant of a daunomycin--Poly d(GCAT)-Poly d(ATGC) complex. Y.Z. Chen and E.W. Prohofsky, Biophys. J. 66, 820 (1994).
  127. Near-neighbor effects in cooperative modified selfconsistent phonon approximation melting in DNA. Y.Z. Chen and E.W. Prohofsky, Phys. Rev. E 49, 873 (1994).
  128. First or second order transition in the melting of repeat sequence DNA. Y.Z. Chen and E.W. Prohofsky,Biophys. J.66, 202 (1994).
  129. The role of thermal flucatuational base pair disruption in DNA-B to DNA-Z conformation change. Y.Z. Chen and E.W. Prohofsky,Biophys. J.66, A291 (1994).
  130. Theoretical study of the effect of salt and the role of strained hydrogen bonds on the thermal stability of DNA polymers. Y.Z. Chen & E.W. Prohofsky, Phys. Rev. E48, 3099 (1993).
  131. Salt dependent premelting base pair opening probabilities of B and Z DNA Poly[d(G-C)] and significance for the B-Z transition. Y.Z. Chen & E.W. Prohofsky, Biophys. J. 64, 1394 (1993).
  132. Synergistic effects in the melting of DNA hydration shell: Melting of the minor groove hydration spine in Poly(dA)-Poly(dT) and its effect on base pair stability. Y.Z. Chen & E.W. Prohofsky,Biophys. J. 64, 1385 (1993).
  133. Differences in melting behavior between homopolymers and copolymers of DNA: Role of non-bonded forces for GC and the role of the hydration spine and premelting transition for AT. Y.Z. Chen & E.W. Prohofsky, Biopolymers33, 797 (1993).
  134. A cooperative self-consistent microscopic theory of thermally induced melting of a repeat sequence DNA polymer. Y.Z. Chen & E.W. Prohofsky, Biopolymers33, 351 (1993).
  135. Theory of presure-dependent melting of the DNA double helix: Role of strained hydrogen bonds. Y.Z. Chen & E.W. Prohofsky, Phys. Rev. E47, 2100 (1993).
  136. Strained hydrogen-bonds between Poly(dA).Poly(dT) and its hydration spin and its role in base pair stability. Y.Z. Chen and E.W. Prohofsky,Biophys. J.64, A356 (1993).
  137. Description of base motion and role of excitations in the melting of Poly(dG)-Poly(dC). W. Zhuang, Y.Z. Chen & E.W. Prohofsky, J. Biomol. Struc. Dyn. 10, 403 (1992).
  138. Energy flow considerations and thermal fluctuational opening of DNA base pairs at a replicating fork: Unwinding consistent with observed replication rates. Y.Z. Chen, W. Zhuang & E.W. Prohofsky, J. Biomol. Struct. Dynam. 10, 415 (1992).
  139. Salt-dependent stability of Poly(dG)-Poly(dC) with potential of mean force Coulomb interactions. Y.Z. Chen, W. Zhuang & E.W. Prohofsky, Biopolymers32, 1123 (1992).
  140. The role of a minor groove spine of hydration in stabilizing Poly(dA)-Poly(dT) against fluctuational interbase H-bond disruption in the premelting temperature regime. Y.Z. Chen & E.W. Prohofsky,Nucleic. Acids. Res. 20, 415 (1992).
  141. Premelting thermal fluctuational interbase hydrogen bond disrupted states of a B DNA Guanine-Cytosine base pair. Significance for amino and imino proton exchange. Y.Z. Chen, W. Zhuang & E.W. Prohofsky, Biopolymers31, 1273 (1991).
  142. Premelting thermal fluctuational base pair opening probability of Poly(dA)-Poly(dT) as predicted by the modified self-consistent phonon theory. Y.Z. Chen, Y. Feng & E.W. Prohofsky, Biopolymers 31, 139 (1991).
  143. A selfconsistent mean-field calculation of a homopolymer DNA strand separation: bond breaking in a macromolecule. Y.Z. Chen & E.W. Prohofsky, J. Chem. Phys.94, 4665 (1991).
  144. Criterion of thermal denaturation for modified-self-consistent-phonon-theory mean-field calculations in DNA polymers. Y.Z. Chen, Y. Feng & E.W. Prohofsky, Phys. Rev. B42, 11335 (1990).
Publications in the Area of Nonlinear Science
  1. Thermodynamics of Toda lattice models: application to DNA. R.K. Bullough, Y.Z. Chen and J.Timonen, Physica D 68, 83 (1993).
  2. Order and chaos in the statistical mechanics of the integrable models in 1+1 dimensions. R.K. Bullough, Y.Z. Chen and J.Timonen, in: Proc. Intl Meeting `Aspects of Nonlinear Dynamics and solitons and Chaos', eds. I. Antonin and F.J. Lambert, Springer-Verlag, Heidelberg (1991). pp. 25-37.
  3. Exact results in the statistical mechanics of integrable models in (1+1) dimensions. R.K. Bullough, D.J. Pilling, Y.Z. Chen & J. Timonon, in: Exact results in quantum dynamics, eds. J. Dittrich et. al., World Scientific, Singapore (1991).
  4. Nonlinearity and disorder in the statistical mechanics of integrable systems. R.K. Bullough, J. Timonon & Y.Z. Chen, in: Nonlinearity and disorder, eds. A.R. Bishop et. al., Springer-Verlag, Berlin (1991).
  5. Classical thermodynamics of the Heisenberg chain in a field by generalized Bethe ansatz method. R.K. Bullough, Y.Z. Chen, J. Timonon, V. Tognetti & R. Vaia, Phys. Lett. A145, 154 (1990).
  6. Quantum and classical statistical mechanics of the integrable models. R.K. Bullough, Y.Z. Chen, Y. Cheng, D.J. Pilling & J. Timonon, in: Nonlinear evolution equations: integrability and spectral methods, eds. A. Degasperis, A.D. Fordy & M. Lakshmanan. (Manchester Univ. Press, Manchester 1990).
  7. Soliton statistical mechanics -- thermodynamic limits for quantum and classical integrable models. R.K. Bullough, Y.Z. Chen & J. Timonon, in: Nonlinear and turbulent processes in physics, eds. V.G. Baryakhtar, V.M. Chernousenko, N.S. Erokhin & V.E. Zakharov. (World Scientific, Singapore, 1990). pp.1377-1422.
  8. Soliton statistical-mechanics and the thermalization of biological solitons. R.K. Bullough, D.J. Pilling, Y. Cheng, Y.Z. Chen and J. Timonen, , J. Phys. (Paris) 50 (Suppl 3), 41-51 (1989).
  9. Statistical mechanics of the NLS models and their avartars. R.K. Bullough, Y.Z. Chen, S. Olafsson & J. Timonon. in: Integrable systems and applications, eds. M. Balabane, P. Lochak & C. Sulem. (Springer-Verlag, Heidelberg,1989). 12-26.
  10. Soliton statistical mechanics and thermalization of biological solitons. R.K. Bullough, D.J. Pilling, Y. Cheng, Y.Z. Chen & J. Timonon, in: Nonlinear coherent structures in physics, mechanics and biological systems, ed. J. Puget. (E.S.P.C.I (Paris) les editions de physique, Les Uhs, France 1989).
  11. Statistical mechanics of integrable models J. Timonon, Y.Z. Chen & R.K. Bullough, Nucl. Phys. B 5A, 58 (1988).
  12. Recent results on the statistical mechanics of integrable models in 1+1 dimensions. R.K. Bullough, Y.Z. Chen, D.J. Pilling & J. Timonon, in: Plasma theory and nonlinear and turbulent processes in physics, eds. V.G. Bar'yakhtar, V.M. Chernousenko, N.S. Erokhin, A.G. Sitenko & V.E. Zakharov (World Scientific, Singapore, 1988).

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