Y Z Chen

Summary

Affiliation: National University of Singapore
Country: Singapore

Publications

  1. ncbi Ligand-protein inverse docking and its potential use in the computer search of protein targets of a small molecule
    Y Z Chen
    Department of Computational Science, National University of Singapore, Blk S17, Level 7, 3 Science Drive 2, Singapore 117543
    Proteins 43:217-26. 2001
  2. ncbi Can an optimization/scoring procedure in ligand-protein docking be employed to probe drug-resistant mutations in proteins?
    Y Z Chen
    Department of Computational Science, National University of Singapore, Lower Kent Ridge Road, Singapore 119260
    J Mol Graph Model 19:560-70. 2001
  3. ncbi Computer automated prediction of potential therapeutic and toxicity protein targets of bioactive compounds from Chinese medicinal plants
    Y Z Chen
    Department of Computational Science, National University of Singapore, Singapore
    Am J Chin Med 30:139-54. 2002
  4. ncbi Prediction of potential toxicity and side effect protein targets of a small molecule by a ligand-protein inverse docking approach
    Y Z Chen
    Department of Computational Science, National University of Singapore
    J Mol Graph Model 20:199-218. 2001
  5. ncbi MODEL-molecular descriptor lab: a web-based server for computing structural and physicochemical features of compounds
    Z R Li
    Bioinformatics and Drug Design Group, Department of Computational Science, National University of Singapore, Blk SOC1, Level 7, 3 Science Drive 2, Singapore
    Biotechnol Bioeng 97:389-96. 2007
  6. ncbi PEARLS: program for energetic analysis of receptor-ligand system
    L Y Han
    Department of Computational Science, National University of Singapore, Singapore
    J Chem Inf Model 46:445-50. 2006
  7. ncbi PROFEAT: a web server for computing structural and physicochemical features of proteins and peptides from amino acid sequence
    Z R Li
    Bioinformatics and Drug Design Group, Department of Computational Science, National University of Singapore, Blk SOC1, Level 7, 3 Science Drive 2, Singapore 117543
    Nucleic Acids Res 34:W32-7. 2006
  8. ncbi 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
    Bioinformatics and Drug Design Group, Department of Pharmacy, National University of Singapore, Blk S16, Level 8, 3 Science Drive 2, Singapore 117543, Singapore
    J Mol Graph Model 26:1276-86. 2008
  9. ncbi Machine learning approaches for predicting compounds that interact with therapeutic and ADMET related proteins
    H Li
    Bioinformatics and Drug Design Group, Department of Pharmacy and Department of Computational Science, National University of Singapore, Blk S16, Level 8, 3 Science Drive 2, Singapore 117543, Singapore
    J Pharm Sci 96:2838-60. 2007
  10. ncbi MoViES: molecular vibrations evaluation server for analysis of fluctuational dynamics of proteins and nucleic acids
    Z W Cao
    Department of Computational Science, National University of Singapore, Blk SOC1, Level 7, 3 Science Drive 2, Singapore 117543, Singapore
    Nucleic Acids Res 32:W679-85. 2004

Collaborators

Detail Information

Publications71

  1. ncbi Ligand-protein inverse docking and its potential use in the computer search of protein targets of a small molecule
    Y Z Chen
    Department of Computational Science, National University of Singapore, Blk S17, Level 7, 3 Science Drive 2, Singapore 117543
    Proteins 43:217-26. 2001
    ..The application of this approach may facilitate the prediction of unknown and secondary therapeutic target proteins and those related to the side effects and toxicity of a drug or drug candidate. Proteins 2001;43:217-226...
  2. ncbi Can an optimization/scoring procedure in ligand-protein docking be employed to probe drug-resistant mutations in proteins?
    Y Z Chen
    Department of Computational Science, National University of Singapore, Lower Kent Ridge Road, Singapore 119260
    J Mol Graph Model 19:560-70. 2001
    ..More accurate description of ligand-protein interactions and the use of methods such as free energy perturbation and Poisson-Boltzmann may be needed to further improve the quality of prediction...
  3. ncbi Computer automated prediction of potential therapeutic and toxicity protein targets of bioactive compounds from Chinese medicinal plants
    Y Z Chen
    Department of Computational Science, National University of Singapore, Singapore
    Am J Chin Med 30:139-54. 2002
    ....
  4. ncbi Prediction of potential toxicity and side effect protein targets of a small molecule by a ligand-protein inverse docking approach
    Y Z Chen
    Department of Computational Science, National University of Singapore
    J Mol Graph Model 20:199-218. 2001
    ..There are additional 30 predicted targets yet to be validated experimentally. Application of this computer approach can potentially facilitate the prediction of toxicity and side effect of a drug or drug lead...
  5. ncbi MODEL-molecular descriptor lab: a web-based server for computing structural and physicochemical features of compounds
    Z R Li
    Bioinformatics and Drug Design Group, Department of Computational Science, National University of Singapore, Blk SOC1, Level 7, 3 Science Drive 2, Singapore
    Biotechnol Bioeng 97:389-96. 2007
    ..Several testing studies on the computed molecular descriptors are discussed. MODEL is accessible at http://jing.cz3.nus.edu.sg/cgi-bin/model/model.cgi free of charge for academic use...
  6. ncbi PEARLS: program for energetic analysis of receptor-ligand system
    L Y Han
    Department of Computational Science, National University of Singapore, Singapore
    J Chem Inf Model 46:445-50. 2006
    ..PEARLS can be accessed at http://ang.cz3.nus.edu.sg/cgi-bin/prog/rune.pl...
  7. ncbi PROFEAT: a web server for computing structural and physicochemical features of proteins and peptides from amino acid sequence
    Z R Li
    Bioinformatics and Drug Design Group, Department of Computational Science, National University of Singapore, Blk SOC1, Level 7, 3 Science Drive 2, Singapore 117543
    Nucleic Acids Res 34:W32-7. 2006
    ..PROFEAT is accessible at http://jing.cz3.nus.edu.sg/cgi-bin/prof/prof.cgi...
  8. ncbi 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
    Bioinformatics and Drug Design Group, Department of Pharmacy, National University of Singapore, Blk S16, Level 8, 3 Science Drive 2, Singapore 117543, Singapore
    J Mol Graph Model 26:1276-86. 2008
    ..24.3-87.6% of the predicted hits are outside the known hit families. SVM appears to be potentially useful for facilitating lead discovery in VS of large compound libraries...
  9. ncbi Machine learning approaches for predicting compounds that interact with therapeutic and ADMET related proteins
    H Li
    Bioinformatics and Drug Design Group, Department of Pharmacy and Department of Computational Science, National University of Singapore, Blk S16, Level 8, 3 Science Drive 2, Singapore 117543, Singapore
    J Pharm Sci 96:2838-60. 2007
    ..Algorithms for proper representation of the structural and physicochemical properties of compounds are also evaluated...
  10. ncbi MoViES: molecular vibrations evaluation server for analysis of fluctuational dynamics of proteins and nucleic acids
    Z W Cao
    Department of Computational Science, National University of Singapore, Blk SOC1, Level 7, 3 Science Drive 2, Singapore 117543, Singapore
    Nucleic Acids Res 32:W679-85. 2004
    ..MoViES can be accessed at http://ang.cz3.nus.edu.sg/cgi-bin/prog/norm.pl...
  11. ncbi Prediction of functional class of the SARS coronavirus proteins by a statistical learning method
    C Z Cai
    Bioinformatics and Drug Design Group, Department of Computational Science, National University of Singapore, Blk SOC1, Level 7, 3 Science Drive 2, Singapore 117543
    J Proteome Res 4:1855-62. 2005
    ..A web version of our software, SVMProt, is accessible at http://jing.cz3.nus.edu.sg/cgi-bin/svmprot.cgi ...
  12. ncbi Prediction of functional class of novel bacterial proteins without the use of sequence similarity by a statistical learning method
    J Cui
    Bioinformatics and Drug Design Group, Department of Computational Science, National University of Singapore, Singapore
    J Mol Microbiol Biotechnol 9:86-100. 2005
    ..Our study suggests that SVMProt is capable of assigning functional class for novel bacterial proteins at a level not too much lower than that of sequence alignment methods for homologous proteins...
  13. ncbi Homology-free prediction of functional class of proteins and peptides by support vector machines
    F Zhu
    Bioinformatics and Drug Design Group, Department of Pharmacy and Center for Computational Science and Engineering, National University of Singapore, Blk S16, Level 8, 3 Science Drive 2, Singapore
    Curr Protein Pept Sci 9:70-95. 2008
    ..This article evaluates the strategies, current progresses, reported prediction performances, available software tools, and underlying difficulties in using SVM for predicting the functional class of proteins and peptides...
  14. ncbi PharmGED: Pharmacogenetic Effect Database
    C J Zheng
    Department of Pharmacy, Bioinformatics and Drug Design Group, National University of Singapore, Blk S16, Level 8, 3 Science Drive 2, Singapore 117543
    Nucleic Acids Res 35:D794-9. 2007
    ..cz3.nus.edu.sg/phg/ free of charge for academic use. It currently contains 1825 entries covering 108 disease conditions, 266 distinct proteins, 693 polymorphisms, 414 drugs/ligands cited from 856 references...
  15. ncbi Prediction of the functional class of metal-binding proteins from sequence derived physicochemical properties by support vector machine approach
    H H Lin
    Bioinformatics and Drug Design Group, Department of Pharmacy, National University of Singapore, Blk SOC1, Level 7, 3 Science Drive 2, Singapore 117543
    BMC Bioinformatics 7:S13. 2006
    ..These suggest the usefulness of SVM for facilitating the prediction of metal-binding proteins. Our software can be accessed at the SVMProt server http://jing.cz3.nus.edu.sg/cgi-bin/svmprot.cgi...
  16. ncbi Prediction of compounds with specific pharmacodynamic, pharmacokinetic or toxicological property by statistical learning methods
    C W Yap
    Bioinformatics and Drug Design Group, Department of Computational Science, National University of Singapore, Blk SOC1, Level 7, 3 Science Drive 2, Singapore 117543
    Mini Rev Med Chem 6:449-59. 2006
    ..It also evaluates algorithms commonly used for representing structural and physicochemical properties of compounds...
  17. ncbi Prediction of the functional class of lipid binding proteins from sequence-derived properties irrespective of sequence similarity
    H H Lin
    Bioinformatics and Drug Design Group, Department of Computational Science, National University of Singapore, Singapore 117543
    J Lipid Res 47:824-31. 2006
    ..These findings suggest the usefulness of SVMs for facilitating the prediction of lipid binding proteins. Our software can be accessed at the SVMProt server (http://jing.cz3.nus.edu.sg/cgi-bin/svmprot.cgi)...
  18. ncbi Predicting functional family of novel enzymes irrespective of sequence similarity: a statistical learning approach
    L Y Han
    Bioinformatics and Drug Design Group, Department of Computational Science, National University of Singapore, Blk SOC1, Level 7, 3 Science Drive 2, Singapore 117543
    Nucleic Acids Res 32:6437-44. 2004
    ..A web version of our software, SVMProt, is accessible at http://jing.cz3.nus.edu.sg/cgi-bin/svmprot.cgi...
  19. ncbi Prediction of P-glycoprotein substrates by a support vector machine approach
    Y Xue
    Department of Computational Science, National University of Singapore, Blk SOC1, Level 7, 3 Science Drive 2, Singapore 117543
    J Chem Inf Comput Sci 44:1497-505. 2004
    ..5 decision tree, that use the same sets of data and molecular descriptors. Our study indicates the potential of SVM in facilitating the prediction of P-gp substrates...
  20. ncbi Prediction of estrogen receptor agonists and characterization of associated molecular descriptors by statistical learning methods
    H Li
    Bioinformatics and Drug Design Group, Department of Pharmacy, National University of Singapore, Blk SOC1, Level 7, 3 Science Drive 2, Singapore 117543, Singapore
    J Mol Graph Model 25:313-23. 2006
    ..1% for non-agonists. Our study suggests that statistical learning methods such as SVM are potentially useful for facilitating the prediction of ER agonists and for characterizing the molecular descriptors associated with ER agonists...
  21. ncbi Therapeutic targets: progress of their exploration and investigation of their characteristics
    C J Zheng
    Bioinformatics and Drug Design Group, Department of Computational Science, National University of Singapore, Singapore, Singapore
    Pharmacol Rev 58:259-79. 2006
    ..Possible "rules" to guide the search for druggable proteins and the feasibility of using a statistical learning method for predicting druggable proteins directly from their sequences are discussed...
  22. ncbi Usefulness of traditionally defined herbal properties for distinguishing prescriptions of traditional Chinese medicine from non-prescription recipes
    C Y Ung
    Bioinformatics and Drug Design Group, Department of Pharmacy, National University of Singapore, Blk SOC1, Level 7, 3 Science Drive 2, Singapore 117543, Singapore
    J Ethnopharmacol 109:21-8. 2007
    ....
  23. ncbi Regression methods for developing QSAR and QSPR models to predict compounds of specific pharmacodynamic, pharmacokinetic and toxicological properties
    C W Yap
    Bioinformatics and Drug Design Group, Department of Pharmacy, National University of Singapore, Block S4, 18 Science Drive 4, Singapore 117543
    Mini Rev Med Chem 7:1097-107. 2007
    ..Freely available online and commercial software for these regression methods and the areas of their applications are also presented...
  24. ncbi Prediction of MHC-binding peptides of flexible lengths from sequence-derived structural and physicochemical properties
    J Cui
    Bioinformatics and Drug Design Group, Department of Pharmacy and Department of Computational Science, National University of Singapore, Singapore 117543, Republic of Singapore
    Mol Immunol 44:866-77. 2007
    ..01-5% for 24 and 5-8% for 6 alleles) of its constituent peptides are predicted as binders. Our software can be accessed at ...
  25. ncbi Trends in the exploration of anticancer targets and strategies in enhancing the efficacy of drug targeting
    F Zhu
    Department of Pharmacy, National University of Singapore, Singapore
    Curr Mol Pharmacol 1:213-32. 2008
    ..Investigation of the modes of actions of these combinations and targeting methods offers clues to aid the development of more effective anticancer therapies...
  26. ncbi Prediction of genotoxicity of chemical compounds by statistical learning methods
    H Li
    Bioinformatics and Drug Design Group, Department of Computational Science, National University of Singapore, Blk SOC1, Level 7, 3 Science Drive 2, Singapore 117543
    Chem Res Toxicol 18:1071-80. 2005
    ..8% for GT+ and 92.7% for GT- agents. Our study suggests that statistical learning methods, particularly SVM, k-NN, and PNN, are useful for facilitating the prediction of genotoxic potential of a diverse set of molecules...
  27. ncbi Prediction of functional class of novel viral proteins by a statistical learning method irrespective of sequence similarity
    L Y Han
    Bioinformatics and Drug Design Group, Department of Computational Science, National University of Singapore, Block SOC1, Level 7, 3 Science Drive 2, Singapore 117543, Singapore
    Virology 331:136-43. 2005
    ..This suggests that SVMProt to some extent is capable of functional class assignment irrespective of sequence similarity and it is potentially useful for facilitating functional study of novel viral proteins...
  28. ncbi CLiBE: a database of computed ligand binding energy for ligand-receptor complexes
    X Chen
    Department of Computational Science, National University of Singapore
    Comput Chem 26:661-6. 2002
    ..A certain degree of correlation between the computed energy and experimental binding affinity is found, which suggests that the computed energy may be useful in facilitating a qualitative analysis of drug binding competitiveness...
  29. ncbi Prediction of factor Xa inhibitors by machine learning methods
    H H Lin
    Bioinformatics and Drug Design Group, Department of Pharmacy, National University of Singapore, Blk SOC1, Level 7, 3 Science Drive 2, Singapore 117543, Singapore
    J Mol Graph Model 26:505-18. 2007
    ..1% for inhibitors, based-on a more rigorous test with more diverse range of compounds. Our study suggests that machine learning methods such as SVM are useful for facilitating the prediction of FXa inhibitors...
  30. ncbi Prediction of transporter family from protein sequence by support vector machine approach
    H H Lin
    Bioinformatics and Drug Design Group, Department of Computational Science, National University of Singapore, Singapore
    Proteins 62:218-31. 2006
    ..4-99.6% of these are correctly predicted. Our study suggests that the SVM is potentially useful for facilitating functional study of transporters irrespective of sequence similarity...
  31. ncbi Update of KDBI: Kinetic Data of Bio-molecular Interaction database
    Pankaj Kumar
    Bioinformatics and Drug Design Group, Centre for Computational Science and Engineering, National University of Singapore, Blk S16, Level 8, 3 Science Drive 2, Singapore 117543
    Nucleic Acids Res 37:D636-41. 2009
    ..KDBI is publically available at http://bidd.nus.edu.sg/group/kdbi/kdbi.asp...
  32. ncbi Computer prediction of cardiovascular and hematological agents by statistical learning methods
    X Chen
    Bioinformatics and Drug Design Group, Department of Pharmacy, National University of Singapore, Singapore 117543
    Cardiovasc Hematol Agents Med Chem 5:11-9. 2007
    ..It also evaluates algorithms for properly representing and extracting the structural and physicochemical properties of compounds relevant to the prediction of cardiovascular and hematological agents...
  33. ncbi Application of support vector machines to in silico prediction of cytochrome p450 enzyme substrates and inhibitors
    C W Yap
    Bioinformatics and Drug Design Group, Department of Pharmacy and Centre for Computational Science and Engineering, National University of Singapore, Blk S16, Level 8, 3 Science Drive 2, Singapore 117543
    Curr Top Med Chem 6:1593-607. 2006
    ....
  34. ncbi Synergistic therapeutic actions of herbal ingredients and their mechanisms from molecular interaction and network perspectives
    X H Ma
    Department of Pharmacy, National University of Singapore, Singapore
    Drug Discov Today 14:579-88. 2009
    ..Synergistic actions may be responsible for the therapeutic efficacy of a substantial number of herbal products and their mechanisms may be studied by analyzing ingredient-mediated molecular interactions and network regulation...
  35. ncbi Quantitative structure-pharmacokinetic relationships for drug clearance by using statistical learning methods
    C W Yap
    Department of Computational Science, National University of Singapore, Blk SOC1, Level 7, 3 Science Drive 2, Singapore 117543, Singapore
    J Mol Graph Model 24:383-95. 2006
    ..These results suggest that GRNN, SVR, and their consensus model are potentially useful for predicting QSPkR properties of drug leads...
  36. ncbi Prediction of functional class of novel plant proteins by a statistical learning method
    L Y Han
    Department of Computational Science, National University of Singapore, Blk SOC1, Level 7, 3 Science Drive 2, Singapore 117543
    New Phytol 168:109-21. 2005
    ..SVMProt shows a certain level of ability to provide useful hints about the functions of novel plant proteins with no similarity to known proteins...
  37. ncbi SVM-Prot: Web-based support vector machine software for functional classification of a protein from its primary sequence
    C Z Cai
    Department of Computational Science, National University of Singapore, Blk SOC1, Level 7, 3 Science Drive 2, Singapore 117543, Singapore
    Nucleic Acids Res 31:3692-7. 2003
    ..SVMProt can be accessed at http://jing.cz3.nus.edu.sg/cgi-bin/svmprot.cgi...
  38. ncbi Virtual screening of Abl inhibitors from large compound libraries by support vector machines
    X H Liu
    Bioinformatics and Drug Design Group, Department of Pharmacy, Centre for Computational Science and Engineering, National University of Singapore, Blk S16, Level 8, 3 Science Drive 2, Singapore 117543
    J Chem Inf Model 49:2101-10. 2009
    ..These suggest that SVM is capable of searching Abl inhibitors from large compound libraries at low false-hit rates...
  39. ncbi TRMP: a database of therapeutically relevant multiple pathways
    C J Zheng
    Department of Computational Science, National University of Singapore, Blk S17, Level 7, 3 Science Drive 2, Singapore 117543
    Bioinformatics 20:2236-41. 2004
    ..Each entry can be retrieved through multiple methods including multiple pathway name, individual pathway name and disease name. SUPPLEMENTARY INFORMATION: http://bidd.nus.edu.sg/group/trmp/sm.pdf..
  40. ncbi ADME-AP: a database of ADME associated proteins
    L Z Sun
    Department of Computational Science, National University of Singapore, Blk SOC1, Level 7, 3 Science Drive 2, Singapore 117543
    Bioinformatics 18:1699-700. 2002
    ..ADME-AP currently contains entries for 321 proteins and 964 substrates...
  41. ncbi Assessment of approximate string matching in a biomedical text retrieval problem
    J F Wang
    Department of Computational Science, National University of Singapore, Blk SOC1, Level 7, 3 Science Drive 2, Singapore 117543, Singapore
    Comput Biol Med 35:717-24. 2005
    ..9% and 97.3%, respectively. Our study suggests that the Smith-Waterman algorithm is useful for improving the success rate of biomedical text retrieval...
  42. ncbi Trends in the exploration of therapeutic targets for the treatment of endocrine, metabolic and immune disorders
    X Chen
    Bioinformatics and Drug Design Group, Department of Pharmacy, National University of Singapore, Singapore 117543
    Endocr Metab Immune Disord Drug Targets 7:225-31. 2007
    ..Multiple profiles of these targets have been analyzed to probe the sequence, structural, physicochemical and systems-related features contributing to the successful exploration of a target against these diseases...
  43. ncbi Evaluation of virtual screening performance of support vector machines trained by sparsely distributed active compounds
    X H Ma
    Centre for Computational Science and Engineering, National University of Singapore, Singapore
    J Chem Inf Model 48:1227-37. 2008
    ..6%-8.3% of the 19,495-38,483 MDDR compounds similar to the known actives as active. These suggest that SVM has substantial capability in identifying novel active compounds from sparse active data sets at low false-hit rates...
  44. ncbi An integrated mathematical model of thrombin-, histamine-and VEGF-mediated signalling in endothelial permeability
    X N Wei
    Computation and Systems Biology, Singapore MIT Alliance, National University of Singapore, E4 04 10, 4 Engineering Drive 3, 117576, Singapore
    BMC Syst Biol 5:112. 2011
    ..Based on the published ordinary differential equation models of the pathway components, we developed an integrated model of thrombin-, histamine-, and VEGF-mediated MLC activation pathways...
  45. ncbi Classification of a diverse set of Tetrahymena pyriformis toxicity chemical compounds from molecular descriptors by statistical learning methods
    Y Xue
    Bioinformatics and Drug Design Group, Departments of Pharmacy and Computational Science, National University of Singapore, Blk S16, Level 8, 3 Science Drive 2, Singapore 117543
    Chem Res Toxicol 19:1030-9. 2006
    ..These suggest that SLMs are useful for predicting TPT potential of diverse sets of compounds and for characterizing the molecular descriptors associated with TPT...
  46. ncbi KDBI: Kinetic Data of Bio-molecular Interactions database
    Z L Ji
    Department of Computational Science, National University of Singapore, Blk Soc 1, Level 7, 3 Science Drive 2, 117543 Singapore
    Nucleic Acids Res 31:255-7. 2003
    ..Hyperlinks are provided for accessing references in Medline and available 3D structures in PDB and NDB. This database can be accessed at http://xin.cz3.nus.edu.sg/group/kdbi/kdbi.asp...
  47. ncbi Prediction of cytochrome P450 3A4, 2D6, and 2C9 inhibitors and substrates by using support vector machines
    C W Yap
    Department of Computational Science, National University of Singapore, Blk SOC1, Level 7, 3 Science Drive 2, Singapore 117543
    J Chem Inf Model 45:982-92. 2005
    ..These methods generally give better accuracies than single SVM classification systems, and the performance of the PP-CSVM method is slightly better than that of the PM-CSVM method...
  48. ncbi Quantitative Structure-Pharmacokinetic Relationships for drug distribution properties by using general regression neural network
    C W Yap
    Department of Computational Science, National University of Singapore, Blk SOC1, Level 7, 3 Science Drive 2, Singapore 117543
    J Pharm Sci 94:153-68. 2005
    ..749 and 0.089, respectively, and that for milk-plasma distribution are 0.677 and 0.206, 0.224 and 0.647, and 0.201 and 0.587, respectively. These suggest that GRNN is potentially useful for predicting QSPkR properties of chemical agents...
  49. ncbi A computer method for validating traditional Chinese medicine herbal prescriptions
    J F Wang
    Department of Computational Science, National University of Singapore Blk SOCI, Level 7, 3 Science Drivf 2, Singapore
    Am J Chin Med 33:281-97. 2005
    ..7% of these are correctly classified. These accuracies are comparable to those of SVM classification of other biological systems. Our study indicates the potential of SVM for facilitating the analysis of TCM prescriptions...
  50. ncbi Effect of molecular descriptor feature selection in support vector machine classification of pharmacokinetic and toxicological properties of chemical agents
    Y Xue
    Department of Computational Science, National University of Singapore, Blk SOC1, Level 7, 3 Science Drive 2, Singapore 117543
    J Chem Inf Comput Sci 44:1630-8. 2004
    ..Our study suggests that molecular feature selection is useful for improving the speed and, in some cases, the accuracy of statistical learning methods for the prediction of pharmacokinetic and toxicological properties of chemical agents...
  51. ncbi Combinatorial support vector machines approach for virtual screening of selective multi-target serotonin reuptake inhibitors from large compound libraries
    Z Shi
    Bioinformatics and Drug Design Group, Department of Pharmacy, Centre for Computational Science and Engineering, National University of Singapore, Blk S16, Level 8, 3 Science Drive 2, Singapore 117543, Singapore
    J Mol Graph Model 32:49-66. 2012
    ..COMBI-SVM is potentially useful for searching selective multi-target agents without explicit knowledge of these agents...
  52. ncbi Trends in exploration of therapeutic targets
    C J Zheng
    Department of Computational Science, National University of Singapore, Blk Soc 1, Level 7, 3 Science Drive 2, Singapore 117543
    Drug News Perspect 18:109-27. 2005
    ....
  53. ncbi In silico prediction of pregnane X receptor activators by machine learning approaches
    C Y Ung
    Bioinformatics and Drug Design Group, Department of Pharmacy, National University of Singapore, Blk S16, Level 8, 3 Science Drive 2, Singapore 117543
    Mol Pharmacol 71:158-68. 2007
    ..Our systems also correctly predicted 73.3 to 86.7% of 15 newly published hPXR activators. MLMs seem to be useful for predicting PXR activators and for providing clues to physicochemical features of PXR activation...
  54. ncbi Correlation between normal modes in the 20-200 cm-1 frequency range and localized torsion motions related to certain collective motions in proteins
    Z W Cao
    Department of Computational Science, National University of Singapore, 3 Science Drive 2, Singapore 117543, Singapore
    J Mol Graph Model 21:309-19. 2003
    ....
  55. ncbi Prediction of torsade-causing potential of drugs by support vector machine approach
    C W Yap
    Department of Computational Science, National University of Singapore, Blk SOC1, Level 7, 3 Science Drive 2, Singapore 117543
    Toxicol Sci 79:170-7. 2004
    ..This indicates the potential of SVM in facilitating the prediction of TdP-causing risk of small molecules and perhaps other ADRs that involve multiple mechanisms...
  56. ncbi TTD: Therapeutic Target Database
    X Chen
    Department of Computational Science, National University of Singapore, Blk S17, Level 7, 3 Science Drive 2, 117543 Singapore
    Nucleic Acids Res 30:412-5. 2002
    ..Each entry can be retrieved through multiple methods including target name, disease name, drug/ligand name, drug/ligand function and drug therapeutic classification...
  57. ncbi Internet resources related to drug action and human response: a review
    L X Yao
    College of Life Science, Zhejiang University, Hangzhou, Zhejiang, China
    Appl Bioinformatics 5:131-9. 2006
    ..We have reviewed many publicly accessible internet resources of these proteins, according to their roles in drug action and human response, such as therapeutic effect, adverse reaction, absorption, distribution, metabolism and excretion...
  58. ncbi Effect of Xuezhikang, an extract from red yeast Chinese rice, on coronary events in a Chinese population with previous myocardial infarction
    Zongliang Lu
    Fuwai Hospital, Peking Union Medical College, Chinese Academy of Medical Science, Beijing, Peoples Republic of China
    Am J Cardiol 101:1689-93. 2008
    ..In conclusion, long-term therapy with XZK significantly decreased the recurrence of coronary events and the occurrence of new CV events and deaths, improved lipoprotein regulation, and was safe and well tolerated...
  59. ncbi Prevalence of respiratory and atopic disorders in Chinese schoolchildren
    G W Wong
    Department of Paediatrics, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong, China
    Clin Exp Allergy 31:1225-31. 2001
    ..Atopic sensitization is an important factor associated with asthma in Chinese children...
  60. ncbi Traditional Chinese medicine information database
    J F Wang
    Clin Pharmacol Ther 78:92-3. 2005
  61. ncbi Analgesic domains of interferon-alpha
    Y X Wang
    Department of Neurobiology, Institute of Neuroscience, China Medical University, Shenyang, PR China
    Neuroreport 12:857-9. 2001
    ....
  62. ncbi DNA fragmentation factor 45 (DFF45) gene at 1p36.2 is homozygously deleted and encodes variant transcripts in neuroblastoma cell line
    H W Yang
    Department of Pediatrics, Graduate School of Medicine, University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 13-8655, Japan
    Neoplasia 3:165-9. 2001
    ..However, homozygous deletion of the DFF45 gene in the NB-1 cell line may imply the presence of unknown tumor suppressor genes in this region...
  63. ncbi In situ SAXRD study of sol-gel induced well-ordered mesoporous bioglasses for drug delivery
    Y F Zhao
    School of Materials Science and Engineering, Nanyang Technological University, Nanyang Avenue 50, Singapore 639798
    J Biomed Mater Res A 85:1032-42. 2008
    ..The significantly higher loading and better sustained release for P123-MBG, compared to F127-MBG, is attributed to its higher pore volume and surface area...
  64. ncbi Rapid non-genomic inhibitory effects of glucocorticoids on human neutrophil degranulation
    L Liu
    Department of Nautical Medicine, Second Military Medical University, 800 Xiangyin Road, Shanghai, 200433, PR of China
    Inflamm Res 54:37-41. 2005
    ..We infer that these effects may be very important when glucocorticoids act as anti-inflammatory drugs during pulse therapy...
  65. ncbi 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
    Department of Pharmacy, National University of Singapore, Republic of Singapore
    J Control Release 120:211-9. 2007
    ..Possible mechanisms revealed by the QSAR model were discussed...
  66. ncbi Plasma propofol concentrations during orthotopic liver transplantation
    J Wu
    Department of Anesthesiology, 1st Affiliated Hospital of Medical College, Zhejiang University, Hangzhou, China
    Acta Anaesthesiol Scand 49:804-10. 2005
    ....
  67. ncbi Individual allergens as risk factors for asthma and bronchial hyperresponsiveness in Chinese children
    G W K Wong
    Dept of Paediatrics, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region
    Eur Respir J 19:288-93. 2002
    ..However, the difference in the prevalence rate of atopic sensitization cannot explain the higher prevalence of childhood asthma in Hong Kong, when compared with those children from Beijing and Guangzhou...
  68. ncbi Database of traditional Chinese medicine and its application to studies of mechanism and to prescription validation
    X Chen
    College of Life Sciences, Zhejiang University, Hangzhou, Zhejiang, China
    Br J Pharmacol 149:1092-103. 2006
    ..Quantitative information about TCM prescriptions, constituent herbs and herbal ingredients is necessary for studying and exploring TCM...
  69. ncbi Protein function classification via support vector machine approach
    C Z Cai
    Department of Applied Physics, Chongqing University, Chongqing 400044, People's Republic of China
    Math Biosci 185:111-22. 2003
    ..This suggests the usefulness of SVM in the classification of protein functional classes and its potential application in protein function prediction...
  70. ncbi [The design of measure and control system for composite treating instrument of gastrointestinal cancer]
    L An
    Biomedical Instrument Institute, Shanghai Jiao Tong University
    Zhongguo Yi Liao Qi Xie Za Zhi 25:128-9, 127. 2001
    ..A complete set of intelligentialized real-time measure and control system was well designed. The experiment result showed that this system has a stable performance and good real-time...
  71. ncbi Cerebral response to patient's own name in the vegetative and minimally conscious states
    H B Di
    Zhejiang University School of Medicine, Hangzhou 310006, China
    Neurology 68:895-9. 2007
    ....