Dexter Pratt
Impact in
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- Bioinformatics and Genomic Networks
- Gene Regulatory Network Analysis
- Biomedical Text Mining and Ontologies
- Gene expression and cancer classification
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- Computational Drug Discovery Methods
Papers in
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- Bioinformatics and Genomic Networks 18
- Gene expression and cancer classification 5
- Biomedical Text Mining and Ontologies 5
- Genetics, Bioinformatics, and Biomedical Research 4
- Metabolomics and Mass Spectrometry Studies 2
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- Computational Drug Discovery Methods 5
- Co-authors
- Karen Pittman (1 shared paper)Mary Shepherd (1 shared paper)Douglas B. Lenat (1 shared paper)R. Guha (1 shared paper)Trey Ideker (14 shared papers)Rudolf Pillich (10 shared papers)Jing Chen (5 shared papers)Barry Demchak (5 shared papers)
- Journals
- Cell Systems (3 papers)Nucleic Acids Research (2 papers)Bioinformatics (2 papers)PLoS Computational Biology (2 papers)Nature Methods (1 paper)
- Partner nations
- United StatesSwitzerlandGermany
In The Last Decade
Dexter Pratt
29 papers receiving 1.1k citations
Peers
Comparison fields: 5 of 133
- Molecular Biology 616
- Computational Theory and Mathematics 131
- Artificial Intelligence 239
- Biophysics 31
- Cancer Research 63
Countries citing papers authored by Dexter Pratt
This map shows the geographic impact of Dexter Pratt'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 Dexter Pratt with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dexter Pratt more than expected).
Fields of papers citing papers by Dexter Pratt
This network shows the impact of papers produced by Dexter Pratt. 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 Dexter Pratt. The network helps show where Dexter Pratt may publish in the future.
Co-authors
The 25 scholars most cited alongside Dexter Pratt, 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 | 1990 | 266 | |
| 2 | 2015 | 166 | |
| 3 | 2012 | 76 | |
| 4 | 2013 | 68 | |
| 5 | 2011 | 64 | |
| 6 | 2017 | 58 | |
| 7 | 2017 | 55 | |
| 8 | 2020 | 47 | |
| 9 | 1999 | 46 | |
| 10 | 2017 | 40 | |
| 11 | 2020 | 33 | |
| 12 | 2022 | 30 | |
| 13 | 2021 | 28 | |
| 14 | 2010 | 27 | |
| 15 | 2024 | 23 | |
| 16 | 2023 | 21 | |
| 17 | 2021 | 20 | |
| 18 | 2013 | 16 | |
| 19 | 2023 | 15 | |
| 20 | 2025 | 14 |
About Dexter Pratt
Dexter Pratt is a scholar working on Molecular Biology, Computational Theory and Mathematics, Cancer Research, Infectious Diseases and Pulmonary and Respiratory Medicine, having authored 31 papers that have together received 1.2k indexed citations. Recurring topics across this work include Bioinformatics and Genomic Networks (18 papers), Gene expression and cancer classification (5 papers), Computational Drug Discovery Methods (5 papers), Biomedical Text Mining and Ontologies (5 papers), Genetics, Bioinformatics, and Biomedical Research (4 papers), Cancer Genomics and Diagnostics (2 papers), Cancer, Lipids, and Metabolism (2 papers) and Metabolomics and Mass Spectrometry Studies (2 papers). The work is most often cited by research in Molecular Biology (616 citations), Computational Theory and Mathematics (131 citations), Artificial Intelligence (239 citations), Biophysics (31 citations) and Cancer Research (63 citations). Dexter Pratt has collaborated with scholars based in United States, Switzerland and Germany. Frequent co-authors include Karen Pittman, Mary Shepherd, Douglas B. Lenat, R. Guha, Trey Ideker, Rudolf Pillich, Jing Chen, Barry Demchak, Vladimir Rynkov and Keiichiro Ono. Their work appears in journals such as Cell Systems, Nucleic Acids Research, Bioinformatics, PLoS Computational Biology and Nature Methods.
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.