Ka Yee Yeung

5.7k citations
56 papers · 3.7k indexed · 2 hit papers · h-index 21
Topics
Gene expression and cancer classification (29 papers)Bioinformatics and Genomic Networks (26 papers)Gene Regulatory Network Analysis (14 papers)

In The Last Decade

Ka Yee Yeung

53 papers receiving 3.5k citations

Hit Papers

Principal component analysis for clustering gene expressi...200120262009201720012001250500750

Peers

Ka Yee Yeung
Comparison fields: 5 of 192
  • Molecular Biology 2.2k
  • Artificial Intelligence 1.0k
  • Computer Vision and Pattern Recognition 357
  • Genetics 279
  • Statistics and Probability 230
Replace Iftach Nachman with:
Iftach Nachman Israel
Christophe Ambroise France
Frank Emmert‐Streib Austria
Ryan Rifkin United States
Jun Sese Japan
Zengyou He China
Iñaki Inza Spain
Alexander J. Hartemink United States
Walter L. Ruzzo United States
Guido Sanguinetti United Kingdom
Ka Yee Yeung relative to Iftach Nachman Israel Iftach Nachman's profile →
Citations per field
00.5×2.9×
Iftach Nachman · 1×
Citations per year

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

20 of 20 papers shown
#WorkIndexed citations
1 3
2 1
3 7
4 3
5 5
6 7
7 2
8 16
9 5
10 41
11 67
12 14
13 18
14 35
15 81
16 68
17 77
18 136
19 40
20 468

About Ka Yee Yeung

Ka Yee Yeung is a scholar working on Information Systems and Management, Molecular Biology and Biophysics, having authored 56 papers that have together received 3.7k indexed citations. Recurring topics across this work include Gene expression and cancer classification (29 papers), Bioinformatics and Genomic Networks (26 papers) and Gene Regulatory Network Analysis (14 papers). The work is most often cited by research in Artificial Intelligence (1.0k citations), Molecular Biology (2.2k citations) and Statistics and Probability (230 citations). Ka Yee Yeung has collaborated with scholars based in United States, Canada and Czechia. Frequent 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. Their work appears in journals such as Proceedings of the National Academy of Sciences, Nature Communications and Nature Genetics.

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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