Jake Lever
Impact in
- Health Informatics top 10%
- Biophysics top 5%
Papers in
-
- Biomedical Text Mining and Ontologies 12
- Bioinformatics and Genomic Networks 5
- Genetics, Bioinformatics, and Biomedical Research 4
- Genomics and Phylogenetic Studies 2
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- Cancer Genomics and Diagnostics 4
- Co-authors
- Martin I. Krzywinski (6 shared papers)Naomi Altman (5 shared papers)Steven J.M. Jones (8 shared papers)Martin R. Jones (3 shared papers)Jasleen Grewal (2 shared papers)Eric Y. Stutheit-Zhao (1 shared paper)Russ Biagio Altman (6 shared papers)Dixie L. Mager (1 shared paper)
- Journals
- Nature Methods (6 papers)Journal of Biomedical Informatics (4 papers)Bioinformatics (2 papers)Proceedings of the National Academy of Sciences (2 papers)F1000Research (2 papers)
- Partner nations
- CanadaUnited StatesUnited Kingdom
In The Last Decade
Jake Lever
29 papers receiving 2.5k citations
Jake Lever's Hit Papers
Peers
Comparison fields: 5 of 209
- Health Informatics 20
- Biophysics 74
- Molecular Biology 665
- Artificial Intelligence 340
- Analytical Chemistry 92
Countries citing papers authored by Jake Lever
This map shows the geographic impact of Jake Lever'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 Jake Lever with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jake Lever more than expected).
Fields of papers citing papers by Jake Lever
This network shows the impact of papers produced by Jake Lever. 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 Jake Lever. The network helps show where Jake Lever may publish in the future.
Co-authors
The 25 scholars most cited alongside Jake Lever, 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 31 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Principal component analysis Hit paper breakdown → | 2017 | 1093 |
| 2 | Model selection and overfitting Hit paper breakdown → | 2016 | 536 |
| 3 | Classification evaluation Hit paper breakdown → | 2016 | 301 |
| 4 | 2019 | 139 | |
| 5 | 2016 | 111 | |
| 6 | 2019 | 90 | |
| 7 | 2016 | 35 | |
| 8 | 2019 | 35 | |
| 9 | 2016 | 35 | |
| 10 | 2019 | 30 | |
| 11 | 2016 | 26 | |
| 12 | 2022 | 22 | |
| 13 | 2019 | 20 | |
| 14 | 2017 | 20 | |
| 15 | 2021 | 19 | |
| 16 | 2019 | 12 | |
| 17 | 2021 | 8 | |
| 18 | 2017 | 7 | |
| 19 | 2022 | 7 | |
| 20 | 2012 | 6 |
About Jake Lever
Jake Lever is a scholar working on Molecular Biology, Cancer Research, Artificial Intelligence, Genetics and Genetics, having authored 31 papers that have together received 2.6k indexed citations. Recurring topics across this work include Biomedical Text Mining and Ontologies (12 papers), Bioinformatics and Genomic Networks (5 papers), Cancer Genomics and Diagnostics (4 papers), Genetics, Bioinformatics, and Biomedical Research (4 papers), Topic Modeling (4 papers), Genomics and Rare Diseases (3 papers), Genomics and Phylogenetic Studies (2 papers) and Natural Language Processing Techniques (2 papers). The work is most often cited by research in Health Informatics (20 citations), Biophysics (74 citations), Molecular Biology (665 citations), Artificial Intelligence (340 citations) and Analytical Chemistry (92 citations). Jake Lever has collaborated with scholars based in Canada, United States and United Kingdom. Frequent co-authors include Martin I. Krzywinski, Naomi Altman, Steven J.M. Jones, Martin R. Jones, Jasleen Grewal, Eric Y. Stutheit-Zhao, Russ Biagio Altman, Dixie L. Mager, Melika Bonakdar and Taku Komura. Their work appears in journals such as Nature Methods, Journal of Biomedical Informatics, Bioinformatics, Proceedings of the National Academy of Sciences and F1000Research.
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.