个人简介
新加坡国立大学分子生物学专业学士（2001）和计算机专业硕士（2005），并在加拿大多伦多大学获得博士（2011）学位，师从国际著名的细胞-细胞通讯和信号转导专家Tony Pawson院士。在博士攻读期间，致力于研究复杂生物系统和人类疾病的信号转导，并在该领域做出了重要的贡献（Tan et al. Science 2009; Tan et al. Science Signaling 2009, Tan et al. Nature Method 2012）。之后，在奥地利维也纳的分子医学中心（CeMM）参予发展了基于细胞热变换（CETSA）-质谱联用技术的药物靶标解析技术（Huber et al., Nature Method 2015）,开创了药物靶标解析方法的新领域。2015年，应CETSA技术发明人Pär Nordlund教授的邀请，加入了新加坡科技研究局分子与细胞生物学研究所(IMCB, A*STAR)，并发明了可以直接从完整细胞和组织中实时监测蛋白质复合物动态变化的系统技术，该工作于2018年发表于Science杂志 (Tan et al. Science 2018)。目前为止，他已经在国际期刊和会议上发表了30多篇文章，包括在Science, Nature Methods, Science Signaling 和 Bioinformatics 第一或通讯作者的文章，H-index为21。其工作受到了Science, Nature Genetics Review, Nature Methods, F1000Prime, Science Signaling, ACS Chemical Biology 和Cell Systems等杂志的高度评价。目前Tan教授担任Science, Nature Biotechnology, Nature Communication, 和Bioinformatics等高水平杂志的审稿人
近期论文
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1. C.S.H. Tan*, K.D. Go, X. Bisteau, L. Dai, C.H. Yong, N. Prabhu, M.B. Ozturk, Y.T. Lim, L. Sreekumar, J. Lengqvist, V. Tergaonkar, P. Kaldis, R.M. Sobota, P. Nordlund*. Thermal proximity coaggregation for system-wide profiling of protein complex dynamics in cells[J], Science, 2018, 359(6380)
2. C.S.H. Tan, A. Pasculescu, W.A. Lim, T. Pawson*, G.D Bader* R. Linding*, Positive selection of tyrosine loss in metazoan evolution[J], Science, 2009, 325 (5948): 1686-8
3. C.S.H. Tan#, B. Bodenmiller#, A. Pasculescu, M. Jovanovic, M.O. Hengartner, C. Jørgensen, G.D. Bader, R. Aebersold, T. Pawson, R. Linding*, Comparative Analysis Reveals Conserved Protein Phosphorylation Networks Implicated in Multiple Diseases[J], Science Signaling, 2009, 2(81):ra39-ra39
4. C.S.H. Tan*, Sequence, Structure, and Network Evolution of Protein Phosphorylation[J], Science Signaling, 2011, 4(182):mr6,
5. K. V. Huber*, K.M. Olek, A.C. Müller, C.S.H Tan, K.L. Bennett, J. Colinge*, G. Superti-Furga*, Proteome-wide drug and metabolite interaction mapping by thermal-stability profiling[J], Nature Methods, 2015, 12(11): 1055
6. C.S.H. Tan*, G.D. Bader, Phosphorylation sites of higher stoichiometry are more conserved[J], Nature Methods, 2012, 9(4):317
7. Tan S H#*, Zhang Z#, Ng S K, ADVICE: Automated Detection and Validation of Interaction by Co-Evolution[J], Nucleic Acids Research, 2004, 32(Web Server): W69-W72
8. C.S.H. Tan#*, W. Hugo#*, W.K. Sung* and S.K. Ng*, A correlated motif approach for finding short linear motifs from protein interaction networks[J], BMC Bioinformatics, 2006, 7(1):502-0
9. X. Shao#, C.S.H. Tan#, C. Voss, S.S.C. Li, N. Deng#, G.D. Bader*, A regression framework incorporating quantitative and negative interaction data improves quantitative prediction of PDZ domain-peptide interaction from primary sequences[J], Bioinformatics, 2011, 27 (3): 383-390
10. Y.T. Lim#, N. Prabhu#, L. Dai, K.D#. Go, D. Chen, L. Sreekumar, L. Egeblad, S. Eriksson, L. Chen, S. Veerappan, H.L. Teo, C.S.H. Tan, J. Lengqvist, A. Larsson, R.M. Sobota*, P. Nordlund*, An efficient proteome-wide strategy for discovery and characterization of cellular nucleotide-protein interactions[J], PLOS ONE, 2018, 12 (12):e0208273
11. C.S.H. Tan, C. Jørgensen, R. Linding*, Roles of “junk phosphorylation” in modulating biomolecular association of phosphorylated proteins?[J], Cell Cycle, 2010, 9(7):1276-1280
12. C.S.H. Tan, R. Linding*. Experimental and computational tools useful for (re)construction of dynamic kinaseâ substrate networks[J], Proteomics, 2009, 9(23):5233-5242
13. S.K. Ng*, Z. Zhang and S.H. Tan, Integrative approach for computationally inferring protein domain interactions[J], Bioinformatics, 2003, 19(8):923-929
14. S.K. Ng*, Z. Zhang and S.H. Tan, K. Lin, InterDom: a database of putative interacting protein domains for validating predicted protein interactions and complexes[J], Nucleic Acids Research, 2003, 31(1):251-254
15. G. Zhou*, D. Shen, J. Zhang, J. Su, S.H. Tan, C.L. Tan, Recognition of protein and gene names from text using an ensemble of classifiers and effective abbreviation resolution[J], BMC Bioinformatics, 2004, 6(Suppl 1):S7
16. Z. Aung*, S.H. Tan, S.K. Ng and K.L. Tan, PPiClust: Efficient clustering of 3D protein-protein interaction interfaces[J], Journal of Bioinformatics & Computational Biology, 2008, 6(3):415-433
17. M.A.T.M. van Vugt, A.K. Gardino, R. Linding, G.J. Ostheimer, H.C. Reinhardt, S.-E. Ong, C.S.H. Tan, H. Miao, S.M. Keezer, J. Li, T. Pawson, T.A. Lewis, S.A. Carr, S.J. Smerdon, T.R. Brummelkamp, M.B. Yaffe*, A Mitotic Phosphorylation Feedback Network Connects Cdk1, Plk1, 53BP1, and Chk2 to Inactivate the G2/M DNA Damage Checkpoint[J], PLoS Biology, 2010, 8(1):e1000287
18. C. Xu#, J. Jin#, C. Bian, R. Lam, R. Tian, R. Weist, L. You, J. Nie, A. Bochkarev, W. Tempel, C.S.H. Tan, G.A. Wasney, M. Vedadi, G.D. Gish, C.H. Arrowsmith, T. Pawson, X.J. Yang, J. Min*, Sequence-Specific Recognition of a PxLPxI/L Motif by an Ankyrin Repeat Tumbler Lock[J], Science Signaling, 2012, 5(226):ra39-ra39
19. B. Herdy, T. Karonitsch, G.I. Vladimer, C.S.H Tan, A. Stukalov, C. Trefzer, J.W. Bigenzahn, T. Theil, J. Holinka, H.P. Kiener, J. Colinge, K.L. Bennett, G. Superti-Furga*, The RNA-binding protein HuRELAVL1 regulates IFN-βmRNA abundance and the type I IFN response[J], European Journal of Immunology, 2015, 45(5)1500-1511
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