基本情况
姓名： 王林聪

性别： 男
职称： 教授
最高学历： 研究生
最高学位： 博士
详细情况
所在学科专业： 生物信息学
所研究方向： 基于结构的药物设计，计算分子生物学
讲授课程： 计算分子生物学
教育经历： 1986-1990 浙江大学，生命学院，本科/学士
1998年5月于 Michigan State University生物化学系获博士学位。
1999-2001 the University of Maryland, Department of Computer Science, College Park, MD, USA. Master Program.
工作经历： 1998-2000在密歇根大学（The University of Michigan）生物物理研究部 （Biophysics Research Division）跟国际著名核磁共振专家 Prof. Erik R. Zuiderweg 做博士后研究。
2001-2006 加入达特茅斯学院 （Dartmouth College）计算机系做研究助理教授。与国际著名人工智能专家和 计算结构生物学专家，ACM Fellow, Prof. Bruce R. Donald 共事。
2006-2007。在新泽西州立大学 （Rutgers University ）高等生物科技与医药研究中心研究（CABM）做研究助理教授。与国际著名结构生物学专家 Prof. Guy Montelione 共事。
2007-2010。在勃林格-殷格翰(Boehringer Ingelheim)公司药物化学部结构研究组工作。主要研发项目是小分子药物跟蛋白质对接算法的设计、实施和分析， 特别是用高通量的但没有归属的NMR数据来确定配体的模式的算法。期间研发了一套使用高通量实验数据准确地计算对接模式(docking pose)的计算平台。

科研项目： 1. 美国NIH 基金项目 NIH-R01-GM65982 (申请者王林聪是主要参与者)
项目经费: 120 万美元。
项目名称: ＮＭＲ信号自动归属和高通量蛋白质结构。
2. 美国NSF 基金项目 EIA-030544 (申请者王林聪是项目主要参与者)
项目经费: 30 万美元。
项目名称:计算生物学中的算法挑战。
3. 美国NSF 基金项目 EIA-** (申请者王林聪是项目共同主持人)
项目经费: 12 万美元。
项目名称: 物理几何算法（Physical Geometric Algorithms）和高通量NMR结构生物学。

学术论文： •计算机科学会议论文 (conference paper)
[1].S. Xu, S. Zou and L. Wang A Geometric Clustering Algorithm and Its Applications to Structural Data. (RECOMB2014) (acceptance rate 16.7%, RECOMB is one of the most prestigious conferences in computational biology and bioinformatics).
[2].L. Wang (2010) The Geometric and Electrostatic Properties of Binding Cavities and Their Usage in Protein-Ligand Docking.Frontier of Computer Science and Technology, Changchun, China (August 2010) pp. 442–447.
[3].L. Wang and B. R. Donald (2006) A Data-Driven, Systematic Search Algorithm for Structure Determination of Denatured or Disordered Proteins. The Computational Systems Bioinformatics Conference (CSB), Stanford CA (August, 2006) pp. 67–78 (Best Paper Award)。
[4].L. Wang and B. R. Donald (2005). An Efficient and Accurate Algorithm for Assigning Nuclear Overhauser Effect Restraints Using a Rotamer Library Ensemble and Residual Dipolar Couplings. IEEE Computer Society Bioinformatics Conference (CSB2005), Stanford CA (August, 2005) pp. 189–202。
[5].L. Wang, R. Mettu and B. R. Donald (2005). An Algebraic Geometry Approach to Backbone Structure Determination from NMR Data. IEEE Computer Society Bioinformatics Conference. IEEE Computer Society Bioinformatics Conference (CSB2005) Stanford CA (August, 2005) pp. 235–246。
[6].L. Wang and B. R. Donald (2004). Analysis of a Systematic Search-Based Algorithm for Determining Protein Backbone Structure from a Minimal Number of Residual Dipolar Couplings. The IEEE Computational Systems Bioinformatics Conference (CSB2004), Stanford CA (August, 2004) pp. 319-330。
[7].C. Langmead, A. Yan, R. Lilien, L. Wang and B. R. Donald (2003). A Polynomial-Time Nuclear Vector Replacement Algorithm for Automated NMR Resonance Assignments. Proceedings of the Seventh Annual InternationalConference on Research inComputational Molecular Biology (RECOMB2003), 176-187. Berlin, Germany, April 10-13。
[8].L. Wang, R. Mettu, R. Lilien and B. R. Donald (2003). An Exact Algorithm for Determining Protein Backbone Structure from NH Residual Dipolar Couplings. IEEE Computer Society Bioinformatics Conference (CSB2003), 611-612. Stanford, CA, August 11-14. (Best Poster Award)。
•杂志论文 （生物化学，生物物理，结构生物学和计算机科学）
[1].L. Wang, Y, Hou, H. Quan, W. Xu, Y. Bao, Y. Li, Y. Fu, S. Zou (2013) A Compound-Based Computational Approach for the Accurate Determination of Hot Spots. Protein Science 22(8):1060-70.
[2].X. Y. Yuan, D. Y. Fu, X. F. Ren, X. Fang, L. Wang, S. Zou, and Y. Wu (2013) Highly Selective Aza-nitrile Inhibitors for Cathepsin K, Structural Optimization and Molecular Modeling. Org. Biomol. Chem. 11(35):5847-5.
[3].X. F. Ren, H, W. Li, X. Fang, Y. Wu, L. Wang, and S. Zou (2013) Highly Selective Azadipeptide Nitrile Inhibitors for cathepsin K: Design, Synthesis and Activity Assays. Org. Biomol. Chem. 11(7):43-8.
[4].L. Wang, S. Zou, and Y. Wang (2012) Algorithmic challenges in structure-based drug design and NMR structural biology. Front. Electr. Electron. Eng. 7(1):69-84.
[5].J. Zeng, J. Boyles, C. Tripathy, L. Wang, A. Yan, P. Zhou, and B. R. Donald (2009) High-Resolution Protein Structure Determination Starting with a Global Fold Calculated from Exact Solution to the RDC Equations.J. Biomol. NMR, 45(3):265-281.
[6].L. Wang, P. Rossi, C, X. Chen, C. Nwosu, K. Cunningham, L .C. Ma, R. Xiao, J. Liu, M. .C. Baran, G. .T. V. Swapna, T. .B. Acton, R. Burkhard, and G. T. Montelione (2007). Northeast Structural Genomics Consortium Target SiR5 (PDBID 2OA4), RCSB.
[7].L. Wang, P. Rossi, C. .X. Chen, C. Nwosu, K. Cunningham, L .C. Ma, R. Xiao, J. Liu, M. .C. Baran, G. .T. V. Swapna, T. .B. Acton, R. Burkhard, and G. T. Montelione (2007). Northeast Structural Genomics Consortium Target RHR5 (PDBID 2JRT), RCSB.
[8].L. Wang and W. Hu (2006) Residual Dipolar Couplings: Measurements and applications to biomolecular studies. Annual Reports on NMR Spectroscopy, 58: 232–304。
[9].L. Wang, R. Mettu and B. R. Donald (2006). A Polynomial-time Algorithm for De Novo Protein Backbone Structure Determination from NMR Data. Journal of Computational Biology 13(7):1276-1288。
[10].L. Wang and B. R. Donald (2004) Exact Solutions for Internuclear Vectors and Backbone Dihedral Angles from NH Residual Dipolar Couplings in Two Media, and Their Application in a Systematic Search Algorithm for Determining Protein Backbone Structure. J. Biomol. NMR, 29(3):223–242。
[11].C. Langmead, A. Yan, R. Lilien, L. Wang and B. R. Donald (2003). A Polynomial-Time Nuclear Vector Replacement Algorithm for Automated NMR Resonance Assignments. Journal of Computational Biology 11(2–3):277–298。
[12].L. Wang, Y. Pang, T.Holder, J. R. Brender, A. V. Kurochkin, and E. R. P. Zuiderweg (2001) Functional Dynamics in the Active Site of the Ribonuclease Binase. Proceedings of the National Academy of Sciences, USA, 98,7684–7689。
[13].L. Wang, A. V. Kurochkin and E. R. P. Zuiderweg (2000) An Iterative Fitting Procedure for the Determination of Longitudinal NMR Cross-Correlation Rates. J. Magn. Reson. 144,175-185。
[14].M. Pellecchia, Y. Pang, L.Wang, A. V. Kurochkin, A. Kumar and E. R. P. Zuiderweg (1999) Quantitative Measurement of Cross-Correlations Between 15N and 13CO Chemical Shift Anisotropy Relaxation Mechanisms by Multiple Quantum NMR. J. Am. Chem. Soc. 121, 9165-9170。
[15].Y. Pang, L. Wang, M. Pellecchia, A. V. Kurochkin and E. R. P. Zuiderweg (1999) Evidence for Extensive Anisotropic Local Motions in a Small Enzyme Using a New Method to Determine NMR Cross-Correlated Relaxation Rates in the Absence of Resolved Scalar Coupling. J. Biomol. NMR 14(4), 297-306。
[16].L. Wang and H. Yan (1999) NMR Studies of Type II Human Cellular Retinoic Acid Binding Protein. Biochimica et Biophysica Acta 1433, 240-252。
[17].L. Wang, Y. Li, F. Abildgaard, J. L. Markley and H. Yan (1998) NMR Solution Structure of Type II Human Cellular Retinoic Acid Binding Protein: Implications for Ligand Binding. Biochemistry 37, 12727-12736。
[18].L. Wang and H. Yan (1998) NMR Study Suggests a Major Role for Arg111 in Maintaining the Structure and Dynamical Properties of Type II Cellular Retinoic Acid Binding protein. Biochemistry 37. 13021-13032。
[19].X. Chen, M. Tordova, G. L. Gilliland, L. Wang, Y. Li, H. Yan and X. Ji (1998) Crystal Structure of Cellular Retinoic Acid Binding Protein Type II: Suggestions a Mechanism of Ligand Entry. J. Mol. Biol. 278, 641-653。
[20].H. Yan, L. Wang and Y. Li (1997) A Novel Method for Measuring the Binding Properties of the Site-Directed Mutants of The Proteins that Binding Hydrophobic Ligands: Application to Cellular Retinoic Acid Binding Proteins. In Techniques in Protein Chemistry VIII (Marshak D. R. Ed.), 449-456. Academic Press, San Diego。
[21].L. Wang, Y. Li and H. Yan (1997) Human Cellular Retinoic Acid Binding Proteins: Quantitative Analysis of the Ligand Binding Properties of the Wild-Type and Site-Directed Mutants. J. Biol. Chem. 272, 1541-1547。

获奖情况： 最佳论文 (Best Paper) 奖，The Computational Systems Bioinformatics Conference (CSB 2006)，由IEEE计算机学会与美国电脑协会(ACM)联和发起。
最佳会议展板(Best Poster) 奖，The Computational Systems Bioinformatics Conference (CSB 2003)，由IEEE计算机学会与美国电脑协会(ACM)联合发起。
研究奖学金 (Research Fellowship)，密歇根州立大学。