Ka Yee Yeung

5.7k total citations · 2 hit papers
56 papers, 3.7k citations indexed

About

Ka Yee Yeung is a scholar working on Molecular Biology, Computer Networks and Communications and Information Systems and Management. According to data from OpenAlex, Ka Yee Yeung has authored 56 papers receiving a total of 3.7k indexed citations (citations by other indexed papers that have themselves been cited), including 41 papers in Molecular Biology, 7 papers in Computer Networks and Communications and 7 papers in Information Systems and Management. Recurrent topics in Ka Yee Yeung's work include Gene expression and cancer classification (29 papers), Bioinformatics and Genomic Networks (26 papers) and Gene Regulatory Network Analysis (14 papers). Ka Yee Yeung is often cited by papers focused on Gene expression and cancer classification (29 papers), Bioinformatics and Genomic Networks (26 papers) and Gene Regulatory Network Analysis (14 papers). Ka Yee Yeung collaborates with scholars based in United States, Canada and Czechia. Ka Yee Yeung's co-authors include Walter L. Ruzzo, Roger E. Bumgarner, Adrian E. Raftery, David R. Haynor, Chris Fraley, Mario Medvedovic, Alejandro Murua, Raphaël Gottardo, William C. Young and Ling‐Hong Hung and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Communications and Nature Genetics.

In The Last Decade

Ka Yee Yeung

53 papers receiving 3.5k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Principal component analysis for clustering gene expression data

2001 839 citations Ka Yee Yeung, Walter L. Ruzzo Bioinformatics profile →
Model-based clustering and data transformations for gene expression data

2001 572 citations Ka Yee Yeung, Adrian E. Raftery et al. Bioinformatics profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Ka Yee Yeung United States	21	2.2k	1.0k	357	279	230	56	3.7k
Frank Emmert‐Streib Austria	38	2.4k 1.1×	853 0.8×	201 0.6×	262 0.9×	139 0.6×	248	5.4k
Christophe Ambroise France	18	1.1k 0.5×	729 0.7×	214 0.6×	228 0.8×	257 1.1×	50	2.6k
Iftach Nachman Israel	17	3.1k 1.4×	991 0.9×	123 0.3×	318 1.1×	84 0.4×	36	3.9k
Michèl Schummer United States	19	3.0k 1.3×	796 0.8×	377 1.1×	275 1.0×	82 0.4×	26	4.7k
Jun Sese Japan	27	1.9k 0.9×	518 0.5×	280 0.8×	334 1.2×	64 0.3×	82	3.6k
Iñaki Inza Spain	29	2.8k 1.2×	2.9k 2.8×	1.1k 3.0×	219 0.8×	164 0.7×	62	7.4k
Pat Brown United States	8	1.7k 0.7×	599 0.6×	183 0.5×	341 1.2×	196 0.9×	26	3.4k
Zengyou He China	24	1.1k 0.5×	1.5k 1.4×	276 0.8×	154 0.6×	106 0.5×	94	3.1k
Ryan Rifkin United States	17	1.6k 0.7×	1.4k 1.3×	810 2.3×	105 0.4×	123 0.5×	25	3.8k
Jihong Guan China	34	2.2k 1.0×	788 0.8×	293 0.8×	81 0.3×	39 0.2×	292	4.5k

Countries citing papers authored by Ka Yee Yeung

Since Specialization

Citations

This map shows the geographic impact of Ka Yee Yeung'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 Ka Yee Yeung with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ka Yee Yeung more than expected).

Fields of papers citing papers by Ka Yee Yeung

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ka Yee Yeung. 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 Ka Yee Yeung. The network helps show where Ka Yee Yeung may publish in the future.

Co-authorship network of co-authors of Ka Yee Yeung

This figure shows the co-authorship network connecting the top 25 collaborators of Ka Yee Yeung. A scholar is included among the top collaborators of Ka Yee Yeung 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 Ka Yee Yeung. Ka Yee Yeung 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

Sala‐Torra, Olga, Ling‐Hong Hung, Lan Beppu, et al.. (2023). Rapid detection of myeloid neoplasm fusions using single-molecule long-read sequencing. SHILAP Revista de lepidopterología. 3(9). e0002267–e0002267. 3 indexed citations

McCarthy, Mary S., et al.. (2023). A Randomized Controlled Trial of Precision Nutrition Counseling for Service Members at Risk for Metabolic Syndrome. Military Medicine. 188(Supplement_6). 606–613. 1 indexed citations

Hung, Ling‐Hong, et al.. (2022). Cloud-enabled Biodepot workflow builder integrates image processing using Fiji with reproducible data analysis using Jupyter notebooks. Scientific Reports. 12(1). 14920–14920.

Sala‐Torra, Olga, et al.. (2021). A graphical, interactive and GPU-enabled workflow to process long-read sequencing data. BMC Genomics. 22(1). 7 indexed citations

Hung, Ling‐Hong, et al.. (2020). Characterizing Performance Variation of Genomic Data Analysis Workflows on the Public Cloud. 680–683. 1 indexed citations

Hung, Ling‐Hong, et al.. (2019). Holistic optimization of an RNA-seq workflow for multi-threaded environments. Bioinformatics. 35(20). 4173–4175. 3 indexed citations

Young, William C., et al.. (2019). Integration of Multiple Data Sources for Gene Network Inference Using Genetic Perturbation Data. Journal of Computational Biology. 26(10). 1113–1129. 5 indexed citations

Zhang, Pai, Ling‐Hong Hung, Wes Lloyd, & Ka Yee Yeung. (2018). Hot-starting software containers for STAR aligner. GigaScience. 7(8). 7 indexed citations

Hung, Ling‐Hong, et al.. (2017). fastBMA: scalable network inference and transitive reduction. GigaScience. 6(10). 1–10. 5 indexed citations

10.

Hung, Ling‐Hong, et al.. (2017). Reproducible Bioconductor workflows using browser-based interactive notebooks and containers. Journal of the American Medical Informatics Association. 25(1). 4–12. 16 indexed citations

11.

Raftery, Adrian E., et al.. (2015). CyNetworkBMA: a Cytoscape app for inferring gene regulatory networks. University of Washington Tacoma Digital Commons (University of Washington Tacoma). 10(1). 4 indexed citations

12.

Lo, Kenneth, Adrian E. Raftery, Kenneth M. Dombek, et al.. (2012). Integrating external biological knowledge in the construction of regulatory networks from time-series expression data. BMC Systems Biology. 6(1). 101–101. 41 indexed citations

13.

Zarbl, Helmut, Michael A. Gallo, James Glick, Ka Yee Yeung, & Paul Vouros. (2010). The vanishing zero revisited: Thresholds in the age of genomics. Chemico-Biological Interactions. 184(1-2). 273–278. 14 indexed citations

14.

Oehler, Vivian G., et al.. (2009). The derivation of diagnostic markers of chronic myeloid leukemia progression from microarray data. Blood. 114(15). 3292–3298. 78 indexed citations

15.

Gottardo, Raphaël, et al.. (2008). MeV+R: using MeV as a graphical user interface for Bioconductor applications in microarray analysis. Genome biology. 9(7). R118–R118. 81 indexed citations

16.

Gottardo, Raphaël, Adrian E. Raftery, Ka Yee Yeung, & Roger E. Bumgarner. (2005). Bayesian Robust Inference for Differential Gene Expression in Microarrays with Multiple Samples. Biometrics. 62(1). 10–18. 68 indexed citations

17.

Yeung, Ka Yee, Mario Medvedovic, & Roger E. Bumgarner. (2004). From co-expression to co-regulation: how many microarray experiments do we need?. Genome biology. 5(7). R48–R48. 77 indexed citations

18.

Medvedovic, Mario, Ka Yee Yeung, & Roger E. Bumgarner. (2004). Bayesian mixture model based clustering of replicated microarray data. Bioinformatics. 20(8). 1222–1232. 136 indexed citations

19.

Yeung, Ka Yee, Mario Medvedovic, & Roger E. Bumgarner. (2003). Clustering gene-expression data with repeated measurements. Genome biology. 4(5). R34–R34. 157 indexed citations

20.

Yeung, Ka Yee, David R. Haynor, & Walter L. Ruzzo. (2001). Validating clustering for gene expression data. Bioinformatics. 17(4). 309–318. 468 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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