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LIST OF PUBLICATIONS

Publications in the Area of Computational Biology and Drug Design

  1. Chen, Zhen, Wang, Shanshan, Chen, Yuzong. An Iron–Complement Network Model of Thromboinflammation and Humoral Immune Remodeling in Severe COVID-19. Current Issues in Molecular Biology. 48(5), 536. (2026). DOI
  2. Cui, Chao, Su, Xiaorui, Zhang, Zaixi et al.. Activity Cliff-Informed Contrastive Learning for Molecular Property Prediction. (2026). DOI
  3. Lin, Hanbo, Hou, Dongyue, Jiang, Xianhan et al.. NPASS database update 2026: comprehensive quantitative composition, bioactivity, and ADME-Tox data of natural products for biomedical research. Nucleic Acids Research. 54(D1), D1519–D1527. (2025). DOI
  4. TAN, YING, Ying, Huazhang, Wu, Xiang et al.. Molecular-substructure Deep Autoencoders Cluster Biomolecules into Novel Band-Shaped Substructure-Distinguished Bioactivity Clusters in 3D Latent Space. (2025). DOI
  5. Zhang, Yintao, Jiang, Wanghao, Li, Teng et al.. SubCELL: the landscape of subcellular compartment-specific molecular interactions. Nucleic Acids Research. 53(D1), D738–D747. (2024). DOI
  6. Shen, Wanxiang, Cui, Chao, Su, Xiaorui et al.. Activity Cliff-Informed Contrastive Learning for Molecular Property Prediction. (2024). DOI
  7. Lu, Songlin, Huang, Yuanfang, Shen, Wan Xiang et al.. Raman spectroscopic deep learning with signal aggregated representations for enhanced cell phenotype and signature identification. PNAS Nexus. 3(8), (2024). DOI
  8. Zhou, Ying, Zhang, Yintao, Zhao, Donghai et al.. TTD: Therapeutic Target Database describing target druggability information. Nucleic Acids Research. 52(D1), D1465–D1477. (2023). DOI
  9. Zhang, Yintao, Zhou, Ying, Zhou, Yuan et al.. TheMarker: a comprehensive database of therapeutic biomarkers. Nucleic Acids Research. 52(D1), D1450–D1464. (2023). DOI
  10. Wang, Shanshan, Wang, Junyong, Zeng, Xian et al.. Database of space life investigations and information on spaceflight plant biology. Planta. 258(3), (2023). DOI
  11. Cheng, Kai Ping, Shen, Wan Xiang, Jiang, Yu Yang et al.. Deep learning of 2D-Restructured gene expression representations for improved low-sample therapeutic response prediction. Computers in Biology and Medicine. 164, 107245. (2023). DOI
  12. Wang, Tianyi, Tan, Ying, Chen, Yu Zong et al.. Infrared Spectral Analysis for Prediction of Functional Groups Based on Feature-Aggregated Deep Learning. Journal of Chemical Information and Modeling. 63(15), 4615–4622. (2023). DOI
  13. Shen, Wan Xiang, Cui, Chao, Shi, Xiang Cheng et al.. Online triplet contrastive learning enables efficient cliff awareness in molecular activity prediction. (2023). DOI
  14. Shen, Wan Xiang, Liang, Shu Ran, Jiang, Yu Yang et al.. Enhanced metagenomic deep learning for disease prediction and consistent signature recognition by restructured microbiome 2D representations. Patterns. 4(1), 100658. (2023). DOI
  15. Wang, Shanshan, Chen, Yu Zong, Fu, Songsen et al.. In silico approaches uncovering the systematic function of N-phosphorylated proteins in human cells. Computers in Biology and Medicine. 151, 106280. (2022). DOI
  16. Yuyao Jin, Nan Du, Yuanfang Huang et al.. Fluorescence Analysis of Circulating Exosomes for Breast Cancer Diagnosis Using a Sensor Array and Deep Learning. ACS. (2022). DOI
  17. Wan Xiang Shen, Yu Liu, Yan Chen et al.. AggMapNet. Nucleic Acids Research. (2022). DOI
  18. Ying Zhou, Yintao Zhang, Xichen Lian et al.. Therapeutic target database update 2022: facilitating drug discovery with enriched comparative data of targeted agents. Nucleic Acids Research. (2021). DOI
  19. Wang, Shanshan, Zeng, Xian, Wang, Yali et al.. Immunometabolism and potential targets in severe COVID-19 peripheral immune responses. Asian Journal of Pharmaceutical Sciences. 16(6), 665–667. (2021). DOI
  20. Nicole WanNi Tay, Fanxi Liu, Chaoxin Wang et al.. Protein music of enhanced musicality by music style guided exploration of diverse amino acid properties. Heliyon. 7(9), e07933. (2021). DOI
  21. Shen, Wan Xiang, Zeng, Xian, Zhu, Feng et al.. Out-of-the-box deep learning prediction of pharmaceutical properties by broadly learned knowledge-based molecular representations. Nature Machine Intelligence. 3(4), 334–343. (2021). DOI
  22. Chen, Shangying, Yang, Sheng Yong, Zeng, Xian et al.. Combining kinase inhibitors for optimally co‐targeting cancer and drug escape by exploitation of drug target promiscuities. Drug Development Research. 82(1), 133–142. (2020). DOI
  23. Shanshan Wang, Xian Zeng, Yali Wang et al.. East meets West in COVID. Pharmacological Research. 159, 105008. (2020). DOI
  24. Zeng, X., Zhang, P., Wang, Y. et al.. CMAUP: A database of collective molecular activities of useful plants. Nucleic Acids Research. 47(D1), D1118-D1127. (2019).
  25. Yuan, Z., Chen, S., Gao, C. et al.. Development of a versatile DNMT and HDAC inhibitor C02S modulating multiple cancer hallmarks for breast cancer therapy. Bioorganic Chemistry. 87, 200-208. (2019).
  26. Chen, X., Gao, D., Sun, Q. et al.. Metabolic Profiling of Amino Acids by Liquid Chromatography?Tandem Mass Spectrometry (LC?MS) to Characterize the Significance of Glutamine in Triple-Negative Breast Cancer (TNBC). Analytical Letters. 52(7), 1068-1082. (2019).
  27. Chen, Y., Tan, Y., Tan, C. et al.. Naphthalimide-containing conjugated polyelectrolytes with different chain configurations. Organic and Biomolecular Chemistry. 17(10), 2635-2639. (2019).
  28. Wei, Q., Zhao, L., Jiang, L. et al.. Prognostic relevance of miR-137 and its liver microenvironment regulatory target gene AFM in hepatocellular carcinoma. Journal of Cellular Physiology. 234(7), 11888-11899. (2019).
  29. Shangying Chen, Sheng Yong Yang, Zhe Chen et al.. Cover Image, Volume 80, Issue 2. Drug Development Research. 80(2), i--i. (2018). DOI
  30. Chen, Shangying, Yang, Sheng Yong, Chen, Zhe et al.. Drug sales confirm clinical advantage of multi‐target inhibition of drug escapes by anticancer kinase inhibitors. Drug Development Research. 80(2), 246–252. (2018). DOI
  31. Tingting Fu, Guoxun Zheng, Gao Tu et al.. Exploring the Binding Mechanism of Metabotropic Glutamate Receptor 5 Negative Allosteric Modulators in Clinical Trials by Molecular Dynamics Simulations. ACS. 9(6), 1492--1502. (2018). DOI
  32. Lim, V.J.Y., Du, W., Chen, Y.Z. et al.. A benchmarking study on virtual ligand screening against homology models of human GPCRs. Proteins: Structure, Function and Bioinformatics. 86(9), 978-989. (2018).
  33. Zhang, W., Zhang, C., Liu, F. et al.. Antiproliferative activities of the second-generation antipsychotic drug sertindole against breast cancers with a potential application for treatment of breast-to-brain metastases. Scientific Reports. 8(1), (2018).
  34. Yu, C.Y., Li, X.X., Yang, H. et al.. Assessing the Performances of Protein Function Prediction Algorithms from the Perspectives of Identification Accuracy and False Discovery Rate. International journal of molecular sciences. 19(1), (2018).
  35. Zhu, F., Li, X.X., Yang, S.Y. et al.. Clinical Success of Drug Targets Prospectively Predicted by In Silico Study. Trends in Pharmacological Sciences. 39(3), 229-231. (2018).
  36. Zheng, G., Yang, F., Fu, T. et al.. Computational characterization of the selective inhibition of human norepinephrine and serotonin transporters by an escitalopram scaffold. Physical Chemistry Chemical Physics. 20(46), 29513-29527. (2018).
  37. Xue, W., Wang, P., Tu, G. et al.. Computational identification of the binding mechanism of a triple reuptake inhibitor amitifadine for the treatment of major depressive disorder. Physical Chemistry Chemical Physics. 20(9), 6606-6616. (2018).
  38. Xiao, T., Qi, X., Chen, Y. et al.. Development of Ligand-based Big Data Deep Neural Network Models for Virtual Screening of Large Compound Libraries. Molecular informatics. 37(11), e1800031. (2018).
  39. Shao, Y.-M., Ma, X., Paira, P. et al.. Discovery of indolylpiperazinylpyrimidines with dual-target profiles at adenosine A 2A and dopamine D 2 receptors for Parkinson?s disease treatment. PLoS ONE. 13(1), (2018).
  40. Fu, J., Tang, J., Wang, Y. et al.. Discovery of the consistently well-performed analysis chain for swath-ms based pharmacoproteomic quantification. Frontiers in Pharmacology. 9(JUN), (2018).
  41. Zeng, X., Zhang, P., He, W. et al.. NPASS: Natural product activity and species source database for natural product research, discovery and tool development. Nucleic Acids Research. 46(D1), D1217-D1222. (2018).
  42. Li, W., Gao, C., Zhao, L. et al.. Phthalimide conjugations for the degradation of oncogenic PI3K. European Journal of Medicinal Chemistry. 151, 237-247. (2018).
  43. Li, Y.H., Yu, C.Y., Li, X.X. et al.. Therapeutic target database update 2018: Enriched resource for facilitating bench-to-clinic research of targeted therapeutics. Nucleic Acids Research. 46(D1), D1121-D1127. (2018).
  44. Xue, W., Yang, F., Wang, P. et al.. What Contributes to Serotonin-Norepinephrine Reuptake Inhibitors'. ACS Chemical Neuroscience. 9(5), 1128-1140. (2018).
  45. Lin Tao, Bohua Wang, Yafen Zhong et al.. Database and Bioinformatics Studies of Probiotics. Journal of Agricultural and Food Chemistry. 65(35), 7599--7606. (2017). DOI
  46. Zhang, P., Tao, L., Zeng, X. et al.. A protein network descriptor server and its use in studying protein, disease, metabolic and drug targeted networks. Briefings in Bioinformatics. 18(6), 1057-1070. (2017).
  47. Yuan, Z., Sun, Q., Li, D. et al.. Design, synthesis and anticancer potential of NSC-319745 hydroxamic acid derivatives as DNMT and HDAC inhibitors. European Journal of Medicinal Chemistry. 134, 281-292. (2017).
  48. Cui, Z., Chen, S., Wang, Y. et al.. Design, synthesis and evaluation of azaacridine derivatives as dual-target EGFR and Src kinase inhibitors for antitumor treatment. European Journal of Medicinal Chemistry. 136, 372-381. (2017).
  49. Wang, P., Zhang, X., Fu, T. et al.. Differentiating Physicochemical Properties between Addictive and Nonaddictive ADHD Drugs Revealed by Molecular Dynamics Simulation Studies. ACS Chemical Neuroscience. 8(6), 1416-1428. (2017).
  50. Wang, P., Fu, T., Zhang, X. et al.. Differentiating physicochemical properties between NDRIs and sNRIs clinically important for the treatment of ADHD. Biochimica et Biophysica Acta - General Subjects. 1861(11), 2766-2777. (2017).
  51. Li, W., Sun, Q., Song, L. et al.. Discovery of 1-(3-aryl-4-chlorophenyl)-3-(p-aryl)urea derivatives against breast cancer by inhibiting PI3K/Akt/mTOR and Hedgehog signalings. European Journal of Medicinal Chemistry. 141, 721-733. (2017).
  52. Chen, S., Qin, C., Sin, J.E. et al.. Discovery of novel dual VEGFR2 and Src inhibitors using a multistep virtual screening approach. Future Medicinal Chemistry. 9(1), 7-24. (2017).
  53. Zeng, X., Tao, L., Zhang, P. et al.. HEROD: A human ethnic and regional specific omics database. Bioinformatics. 33(20), 3276-3282. (2017).
  54. Li, B., Tang, J., Yang, Q. et al.. NOREVA: Normalization and evaluation of MS-based metabolomics data. Nucleic Acids Research. 45(W1), W162-W170. (2017).
  55. Zhang, B., Wu, W., Jiang, Y. et al.. Novel multi-substituted benzyl acridone derivatives as survivin inhibitors for hepatocellular carcinoma treatment. European Journal of Medicinal Chemistry. 129, 337-348. (2017).
  56. Yuan, Z., Chen, S., Sun, Q. et al.. Olaparib hydroxamic acid derivatives as dual PARP and HDAC inhibitors for cancer therapy. Bioorganic and Medicinal Chemistry. 25(15), 4100-4109. (2017).
  57. Zhang, P., Tao, L., Zeng, X. et al.. PROFEAT Update: A Protein Features Web Server with Added Facility to Compute Network Descriptors for Studying Omics-Derived Networks. Journal of Molecular Biology. 429(3), 416-425. (2017).
  58. Zhang, C., Shao, Y.-M., Ma, X. et al.. Pharmacological relationships and ligand discovery of G protein-coupled receptors revealed by simultaneous ligand and receptor clustering. Journal of Molecular Graphics and Modelling. 76, 136-142. (2017).
  59. Huang, L., Jiang, Y., Chen, Y.. Predicting Drug Combination Index and Simulating the Network-Regulation Dynamics by Mathematical Modeling of Drug-Targeted EGFR-ERK Signaling Pathway. Scientific Reports. 7, (2017).
  60. Shen, W., Xiao, T., Chen, S. et al.. Predicting the Enzymatic Hydrolysis Half-lives of New Chemicals Using Support Vector Regression Models Based on Stepwise Feature Elimination. Molecular Informatics. 36(11), (2017).
  61. Zheng, G., Xue, W., Yang, F. et al.. Revealing vilazodone'. Physical Chemistry Chemical Physics. 19(42), 28885-28896. (2017).
  62. Li, D., Yuan, Z., Chen, S. et al.. Synthesis and biological research of novel azaacridine derivatives as potent DNA-binding ligands and topoisomerase II inhibitors. Bioorganic and Medicinal Chemistry. 25(13), 3437-3446. (2017).
  63. Ding, C., Chen, S., Zhang, C. et al.. Synthesis and investigation of novel 6-(1,2,3-triazol-4-yl)-4-aminoquinazolin derivatives possessing hydroxamic acid moiety for cancer therapy. Bioorganic and Medicinal Chemistry. 25(1), 27-37. (2017).
  64. Lv, Y., Wu, J., Wu, P. et al.. A sensitive polymeric dark quencher-based sensing platform for fluorescence ". RSC Advances. 6(48), 42443-42446. (2016).
  65. Li, W., Li, X., Zhang, B. et al.. Current progresses and trends in the development of progesterone receptor modulators. Current Medicinal Chemistry. 23(23), 2507-2554. (2016).
  66. Cui, Z., Li, X., Li, L. et al.. Design, synthesis and evaluation of acridine derivatives as multi-target Src and MEK kinase inhibitors for anti-tumor treatment. Bioorganic and Medicinal Chemistry. 24(2), 261-269. (2016).
  67. Wu, J., Tan, C., Chen, Z. et al.. Fluorescence array-based sensing of nitroaromatics using conjugated polyelectrolytes. Analyst. 141(11), 3242-3245. (2016).
  68. Xue, W., Wang, P., Li, B. et al.. Identification of the inhibitory mechanism of FDA approved selective serotonin reuptake inhibitors: An insight from molecular dynamics simulation study. Physical Chemistry Chemical Physics. 18(4), 3260-3271. (2016).
  69. Naklua, W., Mahesh, K., Chen, Y.Z. et al.. Molecularly imprinted polymer microprobes for manipulating neurological function by regulating temperature-dependent molecular interactions. Process Biochemistry. 51(1), 142-157. (2016).
  70. Li, Y.H., Xu, J.Y., Tao, L. et al.. SVM-prot 2016: A web-server for machine learning prediction of protein functional families from sequence irrespective of similarity. PLoS ONE. 11(8), (2016).
  71. Yang, H., Qin, C., Li, Y.H. et al.. Therapeutic target database update 2016: Enriched resource for bench to clinical drug target and targeted pathway information. Nucleic Acids Research. 44(D1), D1069-D1074. (2016).
  72. Chen, S., Zhang, P., Liu, X. et al.. Towards cheminformatics-based estimation of drug therapeutic index: Predicting the protective index of anticonvulsants using a new quantitative structure-index relationship approach. Journal of Molecular Graphics and Modelling. 67, 102-110. (2016).
  73. Pan, Y., Zheng, M., Zhong, L. et al.. A preclinical evaluation of SKLB261, a multikinase inhibitor of EGFR/Src/VEGFR2, as a therapeutic agent against pancreatic cancer. Molecular Cancer Therapeutics. 14(2), 407-418. (2015).
  74. Naklua, W., Mahesh, K., Aundorn, P. et al.. An imprinted dopamine receptor for discovery of highly potent and selective D3 analogues with neuroprotective effects This article is dedicated to Associate Prof. Dr. Chamnan Patarapanich the occasion of his 65th birthday.. Process Biochemistry. 50(10), 1537-1556. (2015).
  75. Zhang, C., Tao, L., Qin, C. et al.. CFam: A chemical families database based on iterative selection of functional seeds and seed-directed compound clustering. Nucleic Acids Research. 43(D1), D558-D565. (2015).
  76. Tao, L., Zhu, F., Qin, C. et al.. Clustered Distribution of Natural Product Leads of Drugs in the Chemical Space as Influenced by the Privileged Target-Sites. Scientific Reports. 5, (2015).
  77. Tao, L., Zhu, F., Xu, F. et al.. Co-targeting cancer drug escape pathways confers clinical advantage for multi-target anticancer drugs. Pharmacological Research. 102, 123-131. (2015).
  78. Wu, Y., Tan, Y., Wu, J. et al.. Fluorescence array-based sensing of metal ions using conjugated polyelectrolytes. ACS Applied Materials and Interfaces. 7(12), 6882-6888. (2015).
  79. Li, B.-K., He, B., Tian, Z.-Y. et al.. Modeling, predicting and virtual screening of selective inhibitors of MMP-3 and MMP-9 over MMP-1 using random forest classification. Chemometrics and Intelligent Laboratory Systems. 147, 30-40. (2015).
  80. Zhang, B., Chen, K., Wang, N. et al.. Molecular design, synthesis and biological research of novel pyridyl acridones as potent DNA-binding and apoptosis-inducing agents. European Journal of Medicinal Chemistry. 93, 214-226. (2015).
  81. Rao, H., Huangfu, C., Wang, Y. et al.. Physicochemical Profiles of the Marketed Agrochemicals and Clues for Agrochemical Lead Discovery and Screening Library Development. Molecular Informatics. 34(5), 331-338. (2015).
  82. Tao, L., Zhang, P., Qin, C. et al.. Recent progresses in the exploration of machine learning methods as in-silico ADME prediction tools. Advanced Drug Delivery Reviews. 86, 83-100. (2015).
  83. Qin, C., Tao, L., Phang, Y.H. et al.. The Assessment of the Readiness of Molecular Biomarker-Based Mobile Health Technologies for Healthcare Applications. Scientific Reports. 5, (2015).
  84. Zhong, L., Fu, X.-Y., Zou, C. et al.. A preclinical evaluation of a novel multikinase inhibitor, SKLB-329, as a therapeutic agent against hepatocellular carcinoma. International Journal of Cancer. 135(12), 2972-2982. (2014).
  85. Zhou, S., Li, G.-B., Huang, L.-Y. et al.. A prediction model of drug-induced ototoxicity developed by an optimal support vector machine (SVM) method. Computers in Biology and Medicine. 51, 122-127. (2014).
  86. Zhang, C., Qin, C., Tao, L. et al.. A resource for facilitating the development of tools in the education and implementation of genomics-informed personalized medicine. Clinical Pharmacology and Therapeutics. 95(6), 590-591. (2014).
  87. Chen, Y., Kosmas, P., Anwar, P.S. et al.. A touch-communication model of targeted drug delivery. 2014 Asia-Pacific Microwave Conference Proceedings, APMC 2014. 528-530. (2014).
  88. Ding, C., Zhang, C., Zhang, M. et al.. Multitarget inhibitors derived from crosstalk mechanism involving VEGFR2. Future Medicinal Chemistry. 6(16), 1771-1789. (2014).
  89. Tao, L., Zhu, F., Qin, C. et al.. Nature'. Nature Biotechnology. 32(10), 979-980. (2014).
  90. He, M., Tang, K., Wang, B. et al.. Optimization of culture conditions of Bacillus subtilis natto and preparation of freeze-dried powders as a potentially novel antithrombotic probiotic. Journal of Pure and Applied Microbiology. 8(2), 1619-1625. (2014).
  91. Chen, X., Liu, Y., Yang, H.-W. et al.. SKLB-287, A novel oral multikinase inhibitor of EGFR and VEGFR2, Exhibits potent antitumor activity in LoVo colorectal tumor model. Neoplasma. 61(5), 514-522. (2014).
  92. Qin, C., Zhang, C., Zhu, F. et al.. Therapeutic target database update 2014: A resource for targeted therapeutics. Nucleic Acids Research. 42(D1), (2014).
  93. Jin, F., Gao, D., Zhang, C. et al.. Exploration of 1-(3-chloro-4-(4-oxo-4H-chromen-2-yl)phenyl)-3-phenylurea derivatives as selective dual inhibitors of Raf1 and JNK1 kinases for anti-tumor treatment. Bioorganic and Medicinal Chemistry. 21(3), 824-831. (2013).
  94. Jin, F., Gao, D., Wu, Q. et al.. Exploration of N-(2-aminoethyl)piperidine-4-carboxamide as a potential scaffold for development of VEGFR-2, ERK-2 and Abl-1 multikinase inhibitor. Bioorganic and Medicinal Chemistry. 21(18), 5694-5706. (2013).
  95. Li, B.-K., Cong, Y., Yang, X.-G. et al.. In silico prediction of spleen tyrosine kinase inhibitors using machine learning approaches and an optimized molecular descriptor subset generated by recursive feature elimination method. Computers in Biology and Medicine. 43(4), 395-404. (2013).
  96. Han, B.C., Wei, X.N., Zhang, J.X. et al.. MicrobPad MD: Microbial pathogen diagnostic methods database. Infection, Genetics and Evolution. 13(1), 261-266. (2013).
  97. Lang, X.-L., Sun, Q.-S., Chen, Y.-Z. et al.. Novel synthetic 9-benzyloxyacridine analogue as both tyrosine kinase and topoisomerase i inhibitor. Chinese Chemical Letters. 24(8), 677-680. (2013).
  98. Lang, X., Li, L., Chen, Y. et al.. Novel synthetic acridine derivatives as potent DNA-binding and apoptosis-inducing antitumor agents. Bioorganic and Medicinal Chemistry. 21(14), 4170-4177. (2013).
  99. Liu, X., Zhu, F., Ma, X.H. et al.. Predicting targeted polypharmacology for drug repositioning and multi-target drug discovery. Current Medicinal Chemistry. 20(13), 1646-1661. (2013).
  100. Cong, Y., Li, B.-K., Yang, X.-G. et al.. Quantitative structure-activity relationship study of influenza virus neuraminidase A/PR/8/34 (H1N1) inhibitors by genetic algorithm feature selection and support vector regression. Chemometrics and Intelligent Laboratory Systems. 127, 35-42. (2013).
  101. Cheng, X.-Y., Huang, W.-J., Hu, S.-C. et al.. A global characterization and identification of multifunctional enzymes. PLoS ONE. 7(6), (2012).
  102. Zhang, J., Han, B., Wei, X. et al.. A two-step target binding and selectivity support vector machines approach for virtual screening of dopamine receptor subtype-selective ligands. PLoS ONE. 7(6), (2012).
  103. Zhang, J., Jia, J., Zhu, F. et al.. Analysis of bypass signaling in EGFR pathway and profiling of bypass genes for predicting response to anticancer EGFR tyrosine kinase inhibitors. Molecular BioSystems. 8(10), 2645-2656. (2012).
  104. Shi, Z., Ma, X.H., Qin, C. et al.. Combinatorial support vector machines approach for virtual screening of selective multi-target serotonin reuptake inhibitors from large compound libraries. Journal of Molecular Graphics and Modelling. 32, 49-66. (2012).
  105. Han, B., Ma, X., Zhao, R. et al.. Development and experimental test of support vector machines virtual screening method for searching Src inhibitors from large compound libraries. Chemistry Central Journal. 6(1), (2012).
  106. Yan, K., Chen, Y.-Z., Han, J. et al.. Dissipative particle dynamics simulation of field-dependent DNA mobility in nanoslits. Microfluidics and Nanofluidics. 12(1-4), 157-163. (2012).
  107. Zhu, F., Ma, X.H., Qin, C. et al.. Drug discovery prospect from untapped species: Indications from approved natural product drugs. PLoS ONE. 7(7), (2012).
  108. Liu, X., Shi, Z., Xue, Y. et al.. In silico prediction of adverse drug reactions and toxicities based on structural, biological and clinical data. Current Drug Safety. 7(3), 225-237. (2012).
  109. Ma, J., Zhang, X., Ung, C.Y. et al.. Metabolic network analysis revealed distinct routes of deletion effects between essential and non-essential genes. Molecular BioSystems. 8(4), 1179-1186. (2012).
  110. Zou, J., Ji, P., Zhao, Y.-L. et al.. Neighbor communities in drug combination networks characterize synergistic effect. Molecular BioSystems. 8(12), 3185-3196. (2012).
  111. He, J., Yang, G., Rao, H. et al.. Prediction of human major histocompatibility complex class II binding peptides by continuous kernel discrimination method. Artificial Intelligence in Medicine. 55(2), 107-115. (2012).
  112. Ding, H., Chen, Z., Zhang, C. et al.. Synthesis and cytotoxic activity of some novel N-pyridinyl-2-(6- phenylimidazo[2,1-b]thiazol-3-yl)acetamide derivatives. Molecules. 17(4), 4703-4716. (2012).
  113. Wang, W., Zhou, X., He, W. et al.. The interprotein scoring noises in glide docking scores. Proteins: Structure, Function and Bioinformatics. 80(1), 169-183. (2012).
  114. Zhu, F., Shi, Z., Qin, C. et al.. Therapeutic target database update 2012: A resource for facilitating target-oriented drug discovery. Nucleic Acids Research. 40(D1), (2012).
  115. Zhang, X., Ung, C.Y., Lam, S.H. et al.. Toxicogenomic Analysis Suggests Chemical-Induced Sexual Dimorphism in the Expression of Metabolic Genes in Zebrafish Liver. PLoS ONE. 7(12), (2012).
  116. Ma, X.H., Zhu, F., Liu, X. et al.. Virtual screening methods as tools for drug lead discovery from large chemical libraries. Current Medicinal Chemistry. 19(32), 5562-5571. (2012).
  117. Qin, C., Tan, K.L., Zhang, C.L. et al.. What Does It Take to Synergistically Combine Sub-Potent Natural Products into Drug-Level Potent Combinations?. PLoS ONE. 7(11), (2012).
  118. Wei, X.N., Han, B.C., Zhang, J.X. et al.. An Integrated Mathematical Model of Thrombin-, Histamine-and VEGF-Mediated Signalling in Endothelial Permeability. BMC Systems Biology. 5, (2011).
  119. Zhu, F., Qin, C., Tao, L. et al.. Clustered patterns of species origins of nature-derived drugs and clues for future bioprospecting. Proceedings of the National Academy of Sciences of the United States of America. 108(31), 12943-12948. (2011).
  120. Li, Y., Tan, C., Gao, C. et al.. Discovery of benzimidazole derivatives as novel multi-target EGFR, VEGFR-2 and PDGFR kinase inhibitors. Bioorganic and Medicinal Chemistry. 19(15), 4529-4535. (2011).
  121. Li, Z.R., Liu, G.R., Hadjiconstantinou, N.G. et al.. Dispersive transport of biomolecules in periodic energy landscapes with application to nanofilter sieving arrays. Electrophoresis. 32(5), 506-517. (2011).
  122. Kumar, P., Ma, X., Liu, X. et al.. Effect of training data size and noise level on support vector machines virtual screening of genotoxic compounds from large compound libraries. Journal of Computer-Aided Molecular Design. 25(5), 455-467. (2011).
  123. Zhang, C., Tan, C., Zu, X. et al.. Exploration of (S)-3-aminopyrrolidine as a potentially interesting scaffold for discovery of novel Abl and PI3K dual inhibitors. European Journal of Medicinal Chemistry. 46(4), 1404-1414. (2011).
  124. Luan, X., Gao, C., Zhang, N. et al.. Exploration of acridine scaffold as a potentially interesting scaffold for discovering novel multi-target VEGFR-2 and Src kinase inhibitors. Bioorganic and Medicinal Chemistry. 19(11), 3312-3319. (2011).
  125. Ye, H., Ye, L., Kang, H. et al.. HIT: Linking herbal active ingredients to targets. Nucleic Acids Research. 39(SUPPL. 1), (2011).
  126. Huang, L., Pan, C.Q., Li, B. et al.. Simulating EGFR-ERK signaling control by scaffold proteins KSR and MP1 reveals differential Ligand-Sensitivity Co-Regulated by CBL-CIN85 and Endophilin. PLoS ONE. 6(8), (2011).
  127. Liu, X., Zhu, F., Ma, X. et al.. The Therapeutic Target Database: An Internet resource for the primary targets of approved, clinical trial and experimental drugs. Expert Opinion on Therapeutic Targets. 15(8), 903-912. (2011).
  128. Rao, H.B., Zhu, F., Yang, G.B. et al.. Update of PROFEAT: A web server for computing structural and physicochemical features of proteins and peptides from amino acid sequence. Nucleic Acids Research. 39(SUPPL. 2), (2011).
  129. Tao, L., Yuzong, C., Xiang-Yuan, L.. An insight into the opening path to semi-open conformation of HIV-1 protease by molecular dynamics simulation. AIDS. 24(8), 1121-1125. (2010).
  130. Yap, K.Y.-L., Chan, A., Chui, W.K. et al.. Cancer informatics for the clinician: An interaction database for chemotherapy regimens and antiepileptic drugs. Seizure. 19(1), 59-67. (2010).
  131. Yang, G.-B., Li, Z.-R., Rao, H.-B. et al.. Classification models for acetylcholinesterase inhibitors based on machine learning methods. Wuli Huaxue Xuebao/ Acta Physico - Chimica Sinica. 26(12), 3351-3359. (2010).
  132. Wei, X., Chen, Y.. Computational model of VEGF, thrombin and histamine signalling network. 2010 IEEE International Conference on Bioinformatics and Biomedicine Workshops, BIBMW 2010. 847-848. (2010).
  133. Rao, H., Li, Z., Li, X. et al.. Identification of small molecule aggregators from large compound libraries by support vector machines. Journal of Computational Chemistry. 31(4), 752-763. (2010).
  134. Liu, X.H., Song, H.Y., Zhang, J.X. et al.. Identifying novel type ZBGs and nonhydroxamate HDAC inhibitors through a SVM based virtual screening approach. Molecular Informatics. 29(5), 407-420. (2010).
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  266. Lakshmi, B.S., Kangueane, P., Guo, Y. et al.. Molecular basis for the stereospecificity of Candida rugosa lipase (CRL) towards ibuprofen. Biocatalysis and Biotransformation. 17(6), 475-486. (2000).
  267. Chen, Y.Z., Mohan, V., Griffey, R.H.. Spontaneous base flipping in DNA and its possible role in methyltransferase binding. Physical Review E - Statistical Physics, Plasmas, Fluids, and Related Interdisciplinary Topics. 62(1 B), 1133-1137. (2000).
  268. Chen, Y.Z., Mohan, V., Griffey, R.H.. Effect of backbone ? torsion angle on low energy single base opening in B-DNA crystal structures. Chemical Physics Letters. 287(5-6), 570-574. (1998).
  269. Chen, W., Chen, Y., Hu, G.. The determination of melatonin in health-caring medicine for specific purposes by high performance liquid chromatography-mass spectrometry. Se pu = Chinese journal of chromatography / Zhongguo hua xue hui. 16(5), 451-453. (1998).
  270. Chen, Y.Z., Mohan, V., Griffey, R.H.. The opening of a single base without perturbations of neighboring nucleotides: A study on crystal b-dna duplex d(cgcgaattcgcg)2. Journal of Biomolecular Structure and Dynamics. 15(4), 765-777. (1998).
  271. Steinke, C.A., Reeves, K.K., Powell, J.W. et al.. Vibrational analysis of phosphorothioate dna: Ii. the pos group in the model compound dimethyl phosphorothioate [(ch3O)2(POS)]. Journal of Biomolecular Structure and Dynamics. 14(4), 509-516. (1997).
  272. Chen, Y.Z., Powell, J.W., Prohofsky, E.W.. 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. Biophysical Journal. 72(3), 1327-1334. (1997).
  273. Tompa, G.S., Shen, D., Zhang, C. et al.. Advanced interactive personal computer-based process control systems for oxide MOCVD systems. Materials Research Society Symposium - Proceedings. 415, 167-172. (1996).
  274. Chen, Y.Z., Prohofsky, E.W.. Melting profile and temperature dependent binding constant of an anticancer drug daunomycin-DNA complex. European Biophysics Journal. 24(4), 203-212. (1996).
  275. Chen, Y.Z., Prohofsky, E.W.. Sequence and temperature effect on hydrogen bond disruption in DNA determined by a statistical analysis. European Biophysics Journal. 25(1), 9-18. (1996).
  276. Chen, Y.Z., Prohofsky, E.W.. Calculation of the dynamics of drug binding in a netropsin-DNA complex. Physical Review E. 51(5), 5048-5057. (1995).
  277. Chen, Y.Z., Prohofsky, E.W.. Normal mode calculation of a netropsin?DNA complex: Effect of structural deformation on vibrational spectrum. Biopolymers. 35(6), 657-666. (1995).
  278. Chen, Y.Z., Prohofsky, E.W.. 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. Biopolymers. 35(6), 573-582. (1995).
  279. Chen, Y.Z., Prohofsky, E.W.. First- or second-order transition in the melting of repeat sequence DNA. Biophysical Journal. 66(1), 202-206. (1994).
  280. Chen, Y.Z., Prohofsky, E.W.. Near-neighbor effects in cooperative modified self-consistent phonon approximation melting in DNA. Physical Review E. 49(1), 873-881. (1994).
  281. Chen, Y.Z., Prohofsky, E.W.. Nonlinear effects and thermal expansion as expressed in self-consistent phonon calculations on the temperature dependence of a phase change: Application to the B to Z conformation change in DNA. Physical Review E. 49(4), 3444-3451. (1994).
  282. Chen, Y.Z., Prohofsky, E.W.. Premelting base pair opening probability and drug binding constant of a daunomycin-poly d(GCAT).poly d(ATGC) complex. Biophysical Journal. 66(3), 820-826. (1994).
  283. Chen, Y.Z., Prohofsky, E.W.. A cooperative self?consistent microscopic theory of thermally induced melting of a repeat sequence DNA polymer. Biopolymers. 33(3), 351-362. (1993).
  284. Chen, Y.Z., Prohofsky, E.W.. Differences in melting behavior between homopolymers and copolymers of DNA: Role of nonbonded forces for GC and the role of the hydration spine and premelting transition for AT. Biopolymers. 33(5), 797-812. (1993).
  285. Chen, Y.Z., Prohofsky, E.W.. Salt dependent premelting base pair opening probabilities of B and Z DNA Poly [d(G-C)] and significance for the B-Z transition. Biophysical Journal. 64(5), 1394-1397. (1993).
  286. Chen, Y.Z., Prohofsky, E.W.. 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. Biophysical Journal. 64(5), 1385-1393. (1993).
  287. Chen, Y.Z., Prohofsky, E.W.. Theoretical study of the effect of salt and the role of strained hydrogen bonds on the thermal stability of DNA polymers. Physical Review E. 48(4), 3099-3106. (1993).
  288. Chen, Y.Z., Prohofsky, E.W.. Theory of pressure-dependent melting of the DNA double helix: Role of strained hydrogen bonds. Physical Review E. 47(3), 2100-2108. (1993).
  289. Bullough, R.K., Chen, Y.-z., Timonen, J.T.. Thermodynamics of Toda lattice models: application to DNA. Physica D: Nonlinear Phenomena. 68(1), 83-92. (1993).
  290. Zhuang, W., Chen, Y.Z., Prohofsky, E.W.. Description of base motion and role of excitations in the melting of poly(Dg) ? poly(dc). Journal of Biomolecular Structure and Dynamics. 10(2), 403-414. (1992).
  291. Chen, Y.Z., Zhuang, W., Prohofsky, E.W.. Energy flow considerations and thermal fluctuational opening of dna base pairs at a replicating fork: Unwinding consistent with observed replication rates. Journal of Biomolecular Structure and Dynamics. 10(2), 415-427. (1992).
  292. Xu, J., Zhang, G., Chen, S. et al.. In vitro pharmacological properties of fibrinolytic enzymes extracted from the earthworm (Eisenia Foelide). Acta Academiae Medicinae Shanghai. 19(1), 1-4. (1992).
  293. Chen, Y.Z., Zhuang, W., Prohofsky, E.W.. Salt?Dependent stability of poly(dG) ? poly(dC) with potential of mean force coulomb interactions. Biopolymers. 32(8), 1123-1127. (1992).
  294. Chen, Y.Z., Prohofsky, E.W.. The role of a minor groove spine of hydration in stabilizing poly(DA). Poly(DT) against fuctuational interbase H-bond disruption in the premelting temperature regime. Nucleic Acids Research. 20(3), 415-419. (1992).
  295. Chen, Y.Z., Prohofsky, E.W.. A self-consistent mean-field calculation of a homopolymer deoxyribose nucleic acid strand separation: Bond breaking in a macromolecule. The Journal of Chemical Physics. 94(6), 4665-4667. (1991).
  296. Chen, Y.Z., Feng, Y., Prohofsky, W.. Premelting thermal fluctuational base pair opening probability of poly(dA) ? poly(dT) as predicted by the modified self?consistent phonon theory. Biopolymers. 31(2), 139-148. (1991).
  297. Chen, Y.Z., Zhuang, W., Prohofsky, E.W.. Premelting thermal fluctuational interbase hydrogen?bond disrupted states of a B?DNA guanine?cytosine base pair: Significance for amino and imino proton exchange. Biopolymers. 31(11), 1273-1281. (1991).
  298. Bullough, R.K., Chen, Y.-z., Timonen, J. et al.. Classical thermodynamics of the Heisenberg chain in a field by generalized Bethe ansatz method. Physics Letters A. 145(4), 154-158. (1990).
  299. Chen, Y.Z., Feng, Y., Prohofsky, E.W.. Criterion of thermal denaturation for modified-self-consistent-phonon- theory mean-field calculations in DNA polymers. Physical Review B. 42(17), 11335-11338. (1990).
  300. Timonen, J., Chen, Y.-z., Bullough, R.K.. Statistical mechanics of integrable models. Nuclear Physics B (Proceedings Supplements). 5(1), 58-63. (1988).


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).