Michael Yu
Impact in
- Aging top 2%
- Genetics, Aging, and Longevity in Model Organisms
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- Computational Drug Discovery Methods
Papers in
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- Bioinformatics and Genomic Networks 7
- Biomedical Text Mining and Ontologies 4
- Gut microbiota and health 4
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- Complexity and Algorithms in Graphs 2
- Computational Drug Discovery Methods 2
- Co-authors
- Ideker Trey (12 shared papers)Jason F. Kreisberg (5 shared papers)Jianzhu Ma (4 shared papers)Keiichiro Ono (4 shared papers)Roded Sharan (2 shared papers)Barry Demchak (4 shared papers)Samson H. Fong (2 shared papers)Justin Kwang-Lay Huang (2 shared papers)
- Journals
- Cell Systems (3 papers)Cell (3 papers)Genome biology (2 papers)Nature Methods (1 paper)Journal of Combinatorial Optimization (1 paper)
- Partner nations
- United StatesGermanyUnited Kingdom
In The Last Decade
Michael Yu
22 papers receiving 1.9k citations
Michael Yu's Hit Papers
Peers
Comparison fields: 5 of 112
- Aging 93
- Computational Theory and Mathematics 292
- Molecular Biology 1.1k
- Health Informatics 35
- Cancer Research 181
Countries citing papers authored by Michael Yu
This map shows the geographic impact of Michael Yu'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 Michael Yu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael Yu more than expected).
Fields of papers citing papers by Michael Yu
This network shows the impact of papers produced by Michael Yu. 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 Michael Yu. The network helps show where Michael Yu may publish in the future.
Co-authors
The 25 scholars most cited alongside Michael Yu, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 23 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 300 | |
| 2 | Community assessment to advance computational prediction of cancer drug combinations in a pharmacogenomic screen Hit paper breakdown → | 2019 | 263 |
| 3 | 2017 | 233 | |
| 4 | 2018 | 209 | |
| 5 | 2020 | 186 | |
| 6 | 2018 | 122 | |
| 7 | 2018 | 99 | |
| 8 | 2019 | 68 | |
| 9 | 2014 | 67 | |
| 10 | 2015 | 67 | |
| 11 | 2016 | 59 | |
| 12 | 2023 | 57 | |
| 13 | 2021 | 50 | |
| 14 | 2012 | 37 | |
| 15 | 2024 | 37 | |
| 16 | 2024 | 32 | |
| 17 | 2017 | 24 | |
| 18 | 2019 | 18 | |
| 19 | 2017 | 13 | |
| 20 | 2013 | 11 |
About Michael Yu
Michael Yu is a scholar working on Molecular Biology, Computational Theory and Mathematics, Cancer Research, Genetics and Aging, having authored 23 papers that have together received 2k indexed citations. Recurring topics across this work include Bioinformatics and Genomic Networks (7 papers), Biomedical Text Mining and Ontologies (4 papers), Gut microbiota and health (4 papers), Cancer Genomics and Diagnostics (3 papers), Advanced Clustering Algorithms Research (2 papers), Bacteriophages and microbial interactions (2 papers), Complexity and Algorithms in Graphs (2 papers) and Computational Drug Discovery Methods (2 papers). The work is most often cited by research in Aging (93 citations), Computational Theory and Mathematics (292 citations), Molecular Biology (1.1k citations), Health Informatics (35 citations) and Cancer Research (181 citations). Michael Yu has collaborated with scholars based in United States, Germany and United Kingdom. Frequent co-authors include Ideker Trey, Jason F. Kreisberg, Jianzhu Ma, Keiichiro Ono, Roded Sharan, Barry Demchak, Samson H. Fong, Justin Kwang-Lay Huang, Daniel E. Carlin and Pablo Tamayo. Their work appears in journals such as Cell Systems, Cell, Genome biology, Nature Methods and Journal of Combinatorial Optimization.
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.