James C. Mathews
Impact in
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- Lipid metabolism and biosynthesis
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- Cancer Genomics and Diagnostics
Papers in
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- Bioinformatics and Genomic Networks 5
- Gene Regulatory Network Analysis 3
- Gene expression and cancer classification 2
- CRISPR and Genetic Engineering 2
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- Computational Drug Discovery Methods 2
- Co-authors
- Joseph O. Deasy (7 shared papers)Allen Tannenbaum (7 shared papers)Eric J. Duncavage (1 shared paper)John D. Pfeifer (1 shared paper)Saad Nadeem (4 shared papers)Arnold J. Levine (2 shared papers)Jung Hun Oh (3 shared papers)Aleksandra Filipovska (3 shared papers)
- Journals
- Scientific Reports (2 papers)Clinical Breast Cancer (1 paper)Journal of Mathematical Sociology (1 paper)Clinical Kidney Journal (1 paper)IEEE/ACM Transactions on Computational Biology and Bioinformatics (1 paper)
- Partner nations
- United StatesAustraliaUnited Kingdom
In The Last Decade
James C. Mathews
16 papers receiving 221 citations
Peers
Comparison fields: 5 of 68
- Biochemistry 17
- Cancer Research 29
- Molecular Biology 110
- Oncology 35
- Clinical Biochemistry 9
Countries citing papers authored by James C. Mathews
This map shows the geographic impact of James C. Mathews'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 James C. Mathews with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites James C. Mathews more than expected).
Fields of papers citing papers by James C. Mathews
This network shows the impact of papers produced by James C. Mathews. 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 James C. Mathews. The network helps show where James C. Mathews may publish in the future.
Co-authors
The 25 scholars most cited alongside James C. Mathews, 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 | 2014 | 39 | |
| 2 | 2019 | 31 | |
| 3 | 2013 | 30 | |
| 4 | 2020 | 29 | |
| 5 | 2020 | 14 | |
| 6 | 2018 | 14 | |
| 7 | 2022 | 13 | |
| 8 | 2022 | 11 | |
| 9 | 2020 | 10 | |
| 10 | 2018 | 10 | |
| 11 | 2019 | 7 | |
| 12 | 2023 | 6 | |
| 13 | 2019 | 5 | |
| 14 | 2011 | 3 | |
| 15 | 2020 | 2 | |
| 16 | 2001 | 2 |
About James C. Mathews
James C. Mathews is a scholar working on Molecular Biology, Computational Theory and Mathematics, Genetics, Oncology and Surgery, having authored 16 papers that have together received 226 indexed citations. Recurring topics across this work include Bioinformatics and Genomic Networks (5 papers), Gene Regulatory Network Analysis (3 papers), Gene expression and cancer classification (2 papers), Computational Drug Discovery Methods (2 papers), Genetic Associations and Epidemiology (2 papers), CRISPR and Genetic Engineering (2 papers), Venous Thromboembolism Diagnosis and Management (1 paper) and Cancer Genomics and Diagnostics (1 paper). The work is most often cited by research in Biochemistry (17 citations), Cancer Research (29 citations), Molecular Biology (110 citations), Oncology (35 citations) and Clinical Biochemistry (9 citations). James C. Mathews has collaborated with scholars based in United States, Australia and United Kingdom. Frequent co-authors include Joseph O. Deasy, Allen Tannenbaum, Eric J. Duncavage, John D. Pfeifer, Saad Nadeem, Arnold J. Levine, Jung Hun Oh, Aleksandra Filipovska, Oliver Rackham and Zhouji Chen. Their work appears in journals such as Scientific Reports, Clinical Breast Cancer, Journal of Mathematical Sociology, Clinical Kidney Journal and IEEE/ACM Transactions on Computational Biology and Bioinformatics.
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.