Chris Soon Heng Tan
Chris Soon Heng Tan
Department of Chemistry, Southern University of Science and Technology
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Cited by
Cited by
Genome of Acanthamoeba castellanii highlights extensive lateral gene transfer and early evolution of tyrosine kinase signaling
M Clarke, AJ Lohan, B Liu, I Lagkouvardos, S Roy, N Zafar, C Bertelli, ...
Genome biology 14, 1-15, 2013
A Mitotic Phosphorylation Feedback Network Connects Cdk1, Plk1, 53BP1, and Chk2 to Inactivate the G2/M DNA Damage Checkpoint
MATM van Vugt, AK Gardino, R Linding, GJ Ostheimer, HC Reinhardt, ...
PLoS biology 8 (1), e1000287, 2010
Integrative approach for computationally inferring protein domain interactions
SK Ng, Z Zhang, SH Tan
Proceedings of the 2003 ACM symposium on Applied computing, 115-121, 2003
Proteome-wide drug and metabolite interaction mapping by thermal-stability profiling
KVM Huber, KM Olek, AC Müller, CSH Tan, KL Bennett, J Colinge, ...
Nature methods 12 (11), 1055-1057, 2015
Comparative analysis reveals conserved protein phosphorylation networks implicated in multiple diseases
CSH Tan, B Bodenmiller, A Pasculescu, M Jovanovic, MO Hengartner, ...
Science signaling 2 (81), ra39-ra39, 2009
InterDom: a database of putative interacting protein domains for validating predicted protein interactions and complexes
SK Ng, Z Zhang, SH Tan, K Lin
Nucleic acids research 31 (1), 251-254, 2003
Thermal proximity coaggregation for system-wide profiling of protein complex dynamics in cells
CSH Tan, KD Go, X Bisteau, L Dai, CH Yong, N Prabhu, MB Ozturk, ...
Science 359 (6380), 1170-1177, 2018
Interaction graph mining for protein complexes using local clique merging
XL Li, CS Foo, SH Tan, SK Ng
Genome Informatics 16 (2), 260-269, 2005
Recognition of protein/gene names from text using an ensemble of classifiers
GD Zhou, D Shen, J Zhang, J Su, SH Tan
BMC bioinformatics 6, 1-7, 2005
Positive selection of tyrosine loss in metazoan evolution
CSH Tan, A Pasculescu, WA Lim, T Pawson, GD Bader, R Linding
Science 325 (5948), 1686, 2009
Recent progress in mass spectrometry-based strategies for elucidating protein–protein interactions
TY Low, SE Syafruddin, MA Mohtar, A Vellaichamy, NS A Rahman, ...
Cellular and Molecular Life Sciences 78 (13), 5325-5339, 2021
ADVICE: automated detection and validation of interaction by co-evolution
SH Tan, Z Zhang, SK Ng
Nucleic acids research 32 (suppl_2), W69-W72, 2004
Mutational properties of amino acid residues: implications for evolvability of phosphorylatable residues
P Creixell, EM Schoof, CSH Tan, R Linding
Philosophical Transactions of the Royal Society B: Biological Sciences 367 …, 2012
The RNA‐binding protein HuR/ELAVL1 regulates IFN‐β mRNA abundance and the type I IFN response
B Herdy, T Karonitsch, GI Vladimer, CSH Tan, A Stukalov, C Trefzer, ...
European journal of immunology 45 (5), 1500-1511, 2015
A correlated motif approach for finding short linear motifs from protein interaction networks
SH Tan, W Hugo, WK Sung, SK Ng
BMC bioinformatics 7, 1-16, 2006
Functional centrality: detecting lethality of proteins in protein interaction networks
KL Tew, XL Li, SH Tan
Genome Informatics 19, 166-177, 2007
An efficient proteome-wide strategy for discovery and characterization of cellular nucleotide-protein interactions
YT Lim, N Prabhu, L Dai, KD Go, D Chen, L Sreekumar, L Egeblad, ...
PLoS One 13 (12), e0208273, 2018
Sequence-specific recognition of a PxLPxI/L motif by an ankyrin repeat tumbler lock
C Xu, J Jin, C Bian, R Lam, R Tian, R Weist, L You, J Nie, A Bochkarev, ...
Science signaling 5 (226), ra39-ra39, 2012
Roles of “junk phosphorylation” in modulating biomolecular association of phosphorylated proteins?
CSH Tan, C Jĝrgensen, R Linding
Cell Cycle 9 (7), 1276-1280, 2010
A regression framework incorporating quantitative and negative interaction data improves quantitative prediction of PDZ domain–peptide interaction from primary sequence
X Shao, CSH Tan, C Voss, SSC Li, N Deng, GD Bader
Bioinformatics 27 (3), 383, 2011
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