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For: Goh WWB, Wong L. Design principles for clinical network-based proteomics. Drug Discovery Today 2016;21:1130-8. [DOI: 10.1016/j.drudis.2016.05.013] [Cited by in Crossref: 16] [Cited by in F6Publishing: 17] [Article Influence: 2.7] [Reference Citation Analysis]
Number Citing Articles
1 Wong BJH, Kong W, Wong L, Goh WWB. Resolving missing protein problems using functional class scoring. Sci Rep 2022;12:11358. [PMID: 35790756 DOI: 10.1038/s41598-022-15314-3] [Reference Citation Analysis]
2 Kong W, Wong BJH, Gao H, Guo T, Liu X, Du X, Wong L, Goh WWB. PROTREC: A probability-based approach for recovering missing proteins based on biological networks. J Proteomics 2022;250:104392. [PMID: 34626823 DOI: 10.1016/j.jprot.2021.104392] [Cited by in Crossref: 3] [Cited by in F6Publishing: 1] [Article Influence: 3.0] [Reference Citation Analysis]
3 Tosadori G, Di Silvestre D, Spoto F, Mauri P, Laudanna C, Scardoni G. Analysing omics data sets with weighted nodes networks (WNNets). Sci Rep 2021;11:14447. [PMID: 34262093 DOI: 10.1038/s41598-021-93699-3] [Reference Citation Analysis]
4 Goh WWB, Wong L. The Birth of Bio-data Science: Trends, Expectations, and Applications. Genomics Proteomics Bioinformatics 2020;18:5-15. [PMID: 32428604 DOI: 10.1016/j.gpb.2020.01.002] [Cited by in Crossref: 4] [Cited by in F6Publishing: 3] [Article Influence: 2.0] [Reference Citation Analysis]
5 Ho SY, Wong L, Goh WWB. Avoid Oversimplifications in Machine Learning: Going beyond the Class-Prediction Accuracy. Patterns (N Y) 2020;1:100025. [PMID: 33205097 DOI: 10.1016/j.patter.2020.100025] [Cited by in Crossref: 4] [Cited by in F6Publishing: 6] [Article Influence: 2.0] [Reference Citation Analysis]
6 Wen Bin Goh W, Thalappilly S, Thibault G. Moving beyond the current limits of data analysis in longevity and healthy lifespan studies. Drug Discov Today 2019;24:2273-85. [PMID: 31499187 DOI: 10.1016/j.drudis.2019.08.008] [Reference Citation Analysis]
7 Goh WWB, Wong L. Advanced bioinformatics methods for practical applications in proteomics. Brief Bioinform 2019;20:347-55. [PMID: 30657890 DOI: 10.1093/bib/bbx128] [Cited by in Crossref: 10] [Cited by in F6Publishing: 9] [Article Influence: 3.3] [Reference Citation Analysis]
8 Goh WWB, Wong L. Why breast cancer signatures are no better than random signatures explained. Drug Discov Today 2018;23:1818-23. [PMID: 29864526 DOI: 10.1016/j.drudis.2018.05.036] [Cited by in Crossref: 8] [Cited by in F6Publishing: 9] [Article Influence: 2.0] [Reference Citation Analysis]
9 Zhou L, Wong L, Goh WWB. Understanding missing proteins: a functional perspective. Drug Discovery Today 2018;23:644-51. [DOI: 10.1016/j.drudis.2017.11.011] [Cited by in Crossref: 6] [Cited by in F6Publishing: 7] [Article Influence: 1.5] [Reference Citation Analysis]
10 Goh WWB, Wong L. Dealing with Confounders in Omics Analysis. Trends Biotechnol 2018;36:488-98. [PMID: 29475622 DOI: 10.1016/j.tibtech.2018.01.013] [Cited by in Crossref: 13] [Cited by in F6Publishing: 15] [Article Influence: 3.3] [Reference Citation Analysis]
11 Goh WWB, Sng JC, Yee JY, See YM, Lee TS, Wong L, Lee J. Can Peripheral Blood-Derived Gene Expressions Characterize Individuals at Ultra-high Risk for Psychosis? Comput Psychiatr 2017;1:168-83. [PMID: 30090857 DOI: 10.1162/CPSY_a_00007] [Cited by in Crossref: 12] [Cited by in F6Publishing: 14] [Article Influence: 2.4] [Reference Citation Analysis]
12 Goh WWB, Wong L. NetProt: Complex-based Feature Selection. J Proteome Res 2017;16:3102-12. [PMID: 28664733 DOI: 10.1021/acs.jproteome.7b00363] [Cited by in Crossref: 8] [Cited by in F6Publishing: 12] [Article Influence: 1.6] [Reference Citation Analysis]
13 Goh WWB, Wong L. Class-paired Fuzzy SubNETs: A paired variant of the rank-based network analysis family for feature selection based on protein complexes. Proteomics 2017;17:e1700093. [PMID: 28390171 DOI: 10.1002/pmic.201700093] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 0.2] [Reference Citation Analysis]
14 Goh WW, Wong L. Protein complex-based analysis is resistant to the obfuscating consequences of batch effects --- a case study in clinical proteomics. BMC Genomics 2017;18:142. [PMID: 28361693 DOI: 10.1186/s12864-017-3490-3] [Cited by in Crossref: 9] [Cited by in F6Publishing: 11] [Article Influence: 1.8] [Reference Citation Analysis]
15 Wang W, Sue AC, Goh WWB. Feature selection in clinical proteomics: with great power comes great reproducibility. Drug Discov Today 2017;22:912-8. [PMID: 27988358 DOI: 10.1016/j.drudis.2016.12.006] [Cited by in Crossref: 22] [Cited by in F6Publishing: 21] [Article Influence: 3.7] [Reference Citation Analysis]
16 Goh WW. Fuzzy-FishNET: a highly reproducible protein complex-based approach for feature selection in comparative proteomics. BMC Med Genomics 2016;9:67. [PMID: 28117654 DOI: 10.1186/s12920-016-0228-z] [Cited by in Crossref: 8] [Cited by in F6Publishing: 9] [Article Influence: 1.3] [Reference Citation Analysis]
17 Goh WWB, Wong L. Spectra-first feature analysis in clinical proteomics — A case study in renal cancer. J Bioinform Comput Biol 2016;14:1644004. [DOI: 10.1142/s0219720016440042] [Cited by in Crossref: 3] [Cited by in F6Publishing: 3] [Article Influence: 0.5] [Reference Citation Analysis]