Chee-Keong Kwoh

2.6k total citations
37 papers, 1.6k citations indexed

About

Chee-Keong Kwoh is a scholar working on Molecular Biology, Computational Theory and Mathematics and Artificial Intelligence. According to data from OpenAlex, Chee-Keong Kwoh has authored 37 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 31 papers in Molecular Biology, 11 papers in Computational Theory and Mathematics and 6 papers in Artificial Intelligence. Recurrent topics in Chee-Keong Kwoh's work include Computational Drug Discovery Methods (11 papers), Bioinformatics and Genomic Networks (10 papers) and Gene expression and cancer classification (10 papers). Chee-Keong Kwoh is often cited by papers focused on Computational Drug Discovery Methods (11 papers), Bioinformatics and Genomic Networks (10 papers) and Gene expression and cancer classification (10 papers). Chee-Keong Kwoh collaborates with scholars based in Singapore, China and United Kingdom. Chee-Keong Kwoh's co-authors include Xiaoli Li, Min Wu, See-Kiong Ng, Peng Yang, Jian-Ping Mei, Jie Zheng, Ali Ezzat, Peilin Zhao, Duncan Gillies and Dong Huang and has published in prestigious journals such as Bioinformatics, PLoS ONE and IEEE Access.

In The Last Decade

Chee-Keong Kwoh

36 papers receiving 1.5k citations

Peers

Chee-Keong Kwoh

CTM

Xiaorui Su China

Kexin Huang United States

Xiang Yue China

Huimin Luo China

Alberto Paccanaro United Kingdom

Jiajie Peng China

Jianyang Zeng China

Andreas Mayr Austria

Petteri Hintsanen Finland

Changiz Eslahchi Iran

Xiaorui Su China

Chee-Keong Kwoh

769 ×0.6

549 ×0.7

CTM

156 ×0.7

144 ×1.2

113 ×1.0

Citations per year, relative to Chee-Keong Kwoh Chee-Keong Kwoh (= 1×) peers Xiaorui Su

Countries citing papers authored by Chee-Keong Kwoh

Since Specialization

Citations

This map shows the geographic impact of Chee-Keong Kwoh's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Chee-Keong Kwoh with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chee-Keong Kwoh more than expected).

Fields of papers citing papers by Chee-Keong Kwoh

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Chee-Keong Kwoh. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Chee-Keong Kwoh. The network helps show where Chee-Keong Kwoh may publish in the future.

Co-authorship network of co-authors of Chee-Keong Kwoh

This figure shows the co-authorship network connecting the top 25 collaborators of Chee-Keong Kwoh. A scholar is included among the top collaborators of Chee-Keong Kwoh based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Chee-Keong Kwoh. Chee-Keong Kwoh is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Huang, Dong, Chang‐Dong Wang, Jianhuang Lai, & Chee-Keong Kwoh. (2021). Toward Multidiversified Ensemble Clustering of High-Dimensional Data: From Subspaces to Metrics and Beyond. IEEE Transactions on Cybernetics. 52(11). 12231–12244. 51 indexed citations

Yao, Dengju, et al.. (2019). An improved random forest-based computational model for predicting novel miRNA-disease associations. BMC Bioinformatics. 20(1). 624–624. 36 indexed citations

Yin, Rui, et al.. (2018). A context-free encoding scheme of protein sequences for predicting antigenicity of diverse influenza A viruses. BMC Genomics. 19(S10). 936–936. 29 indexed citations

Ou-Yang, Le, et al.. (2018). Integrating node embeddings and biological annotations for genes to predict disease-gene associations. BMC Systems Biology. 12(S9). 138–138. 22 indexed citations

Zheng, Jie, Fransiskus Xaverius Ivan, Rui Yin, et al.. (2018). Computational analysis of the receptor binding specificity of novel influenza A/H7N9 viruses. BMC Genomics. 19(S2). 88–88. 7 indexed citations

Ezzat, Ali, Min Wu, Xiaoli Li, & Chee-Keong Kwoh. (2018). Computational Prediction of Drug-Target Interactions via Ensemble Learning. Methods in molecular biology. 1903. 239–254. 27 indexed citations

Huang, Dong, Chang‐Dong Wang, Jianhuang Lai, & Chee-Keong Kwoh. (2017). Toward Multi-Diversified Ensemble Clustering of High-Dimensional Data.. arXiv (Cornell University). 1 indexed citations

Ezzat, Ali, Min Wu, Xiaoli Li, & Chee-Keong Kwoh. (2017). Drug-target interaction prediction using ensemble learning and dimensionality reduction. Methods. 129. 81–88. 86 indexed citations

Chen, Haifeng, et al.. (2016). Rules of co-occurring mutations characterize the antigenic evolution of human influenza A/H3N2, A/H1N1 and B viruses. BMC Medical Genomics. 9(S3). 69–69. 10 indexed citations

10.

Lama, Dilraj, Christopher J. Brown, Thomas L. Joseph, et al.. (2016). Water-Bridge Mediates Recognition of mRNA Cap in eIF4E. Structure. 25(1). 188–194. 8 indexed citations

11.

Teh, Ai Ling, Hong Pan, Xinyi Lin, et al.. (2016). Comparison of Methyl-capture Sequencing vs. Infinium 450K methylation array for methylome analysis in clinical samples. Epigenetics. 11(1). 36–48. 36 indexed citations

12.

Yang, Peng, et al.. (2014). Ensemble Positive Unlabeled Learning for Disease Gene Identification. PLoS ONE. 9(5). e97079–e97079. 80 indexed citations

13.

Zhang, Fan, Chee-Keong Kwoh, Min Wu, & Jie Zheng. (2014). Data-driven prediction of cancer cell fates with a nonlinear model of signaling pathways. 436–444. 2 indexed citations

14.

Ellabaan, Mostafa M. H., et al.. (2012). A tree-structured covalent-bond-driven molecular memetic algorithm for optimization of ring-deficient molecules. Computers & Mathematics with Applications. 64(12). 3792–3804. 4 indexed citations

15.

Yang, Peng, Xiaoli Li, Min Wu, Chee-Keong Kwoh, & See-Kiong Ng. (2011). Inferring Gene-Phenotype Associations via Global Protein Complex Network Propagation. PLoS ONE. 6(7). e21502–e21502. 68 indexed citations

16.

Li, Xiaoli, Min Wu, Chee-Keong Kwoh, & See-Kiong Ng. (2010). Computational approaches for detecting protein complexes from protein interaction networks: a survey. BMC Genomics. 11(Suppl 1). S3–S3. 259 indexed citations

17.

Eisenhaber, Frank, Chee-Keong Kwoh, See-Kiong Ng, Wing‐Kin Sung, & Limsoon Wong. (2009). Brief Overview of Bioinformatics Activities in Singapore. PLoS Computational Biology. 5(9). e1000508–e1000508. 5 indexed citations

18.

Kwoh, Chee-Keong, et al.. (2009). Using survival models to analyze the effects of social attributes on length of stay of stroke patients. 18. 1–5. 3 indexed citations

19.

Kwoh, Chee-Keong & Duncan Gillies. (1998). Probabilistic reasoning and multiple-expert methodology for correlated objective data. Artificial Intelligence in Engineering. 12(1-2). 21–33. 4 indexed citations

20.

Kwoh, Chee-Keong & Duncan Gillies. (1996). Using hidden nodes in Bayesian networks. Artificial Intelligence. 88(1-2). 1–38. 37 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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