Kevin Y. Yip
Impact in
- Molecular Biology top 5%
- Genomics and Chromatin Dynamics
- Bioinformatics and Genomic Networks
- RNA and protein synthesis mechanisms
- Epigenetics and DNA Methylation
- Gene expression and cancer classification
- RNA Research and Splicing
- Genomics and Phylogenetic Studies
- RNA modifications and cancer
- Signal Processing top 2%
Papers in
-
- Gene expression and cancer classification 20
- Bioinformatics and Genomic Networks 18
- Genomics and Phylogenetic Studies 17
- RNA modifications and cancer 14
- Genomics and Chromatin Dynamics 14
- RNA and protein synthesis mechanisms 13
- Epigenetics and DNA Methylation 11
- Co-authors
- Mark GersteinBen KaoChao ChengMichael K. NgDavid W. CheungM SnyderTara A. GianoulisKei‐Hoi Cheung
- Journals
- Bioinformatics (14 papers)Genome biology (7 papers)Genome Research (6 papers)Scientific Reports (5 papers)BMC Genomics (5 papers)
- Partner nations
- Hong KongUnited StatesChina
In The Last Decade
Kevin Y. Yip
101 papers receiving 3.3k citations
Peers
Comparison fields: 5 of 168
- Molecular Biology 2.2k
- Signal Processing 264
- Cancer Research 366
- Artificial Intelligence 521
- Genetics 433
Countries citing papers authored by Kevin Y. Yip
This map shows the geographic impact of Kevin Y. Yip'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 Kevin Y. Yip with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kevin Y. Yip more than expected).
Fields of papers citing papers by Kevin Y. Yip
This network shows the impact of papers produced by Kevin Y. Yip. 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 Kevin Y. Yip. The network helps show where Kevin Y. Yip may publish in the future.
Co-authors
The 25 scholars most cited alongside Kevin Y. Yip, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 0 | |
| 2 | 2024 | 2 | |
| 3 | 2024 | 0 | |
| 4 | 2024 | 3 | |
| 5 | 2023 | 5 | |
| 6 | 2023 | 34 | |
| 7 | 2023 | 2 | |
| 8 | 2022 | 5 | |
| 9 | 2022 | 9 | |
| 10 | 2021 | 14 | |
| 11 | 2020 | 53 | |
| 12 | 2020 | 12 | |
| 13 | 2015 | 65 | |
| 14 | 2014 | 3 | |
| 15 | 2012 | 95 | |
| 16 | 2010 | 188 | |
| 17 | 2009 | 9 | |
| 18 | 2008 | 53 | |
| 19 | 2007 | 47 | |
| 20 | 2006 | 14 |
About Kevin Y. Yip
Kevin Y. Yip is a scholar working on Molecular Biology, Cancer Research, Artificial Intelligence, Information Systems and Signal Processing, having authored 106 papers that have together received 3.4k indexed citations. Recurring topics across this work include Gene expression and cancer classification (20 papers), Bioinformatics and Genomic Networks (18 papers), Genomics and Phylogenetic Studies (17 papers), RNA modifications and cancer (14 papers), Genomics and Chromatin Dynamics (14 papers), RNA and protein synthesis mechanisms (13 papers), Data Mining Algorithms and Applications (12 papers) and Epigenetics and DNA Methylation (11 papers). The work is most often cited by research in Molecular Biology (2.2k citations), Signal Processing (264 citations), Cancer Research (366 citations), Artificial Intelligence (521 citations) and Genetics (433 citations). Kevin Y. Yip has collaborated with scholars based in Hong Kong, United States and China. Frequent co-authors include Mark Gerstein, Ben Kao, Chao Cheng, Michael K. Ng, David W. Cheung, M Snyder, Tara A. Gianoulis, Kei‐Hoi Cheung, Joel Rozowsky and David W. Cheung. Their work appears in journals such as Bioinformatics, Genome biology, Genome Research, Scientific Reports and BMC Genomics.
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.