Tom Ryder
Impact in
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- Gene expression and cancer classification
- Advanced biosensing and bioanalysis techniques
- Protein Kinase Regulation and GTPase Signaling
- Molecular Biology Techniques and Applications
- RNA and protein synthesis mechanisms
- Genomics and Chromatin Dynamics
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- Virus-based gene therapy research
Papers in
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- Gene expression and cancer classification 2
- Advanced biosensing and bioanalysis techniques 1
- Molecular Biology Techniques and Applications 1
- Advanced Biosensing Techniques and Applications 1
- Gene Regulatory Network Analysis 1
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- Advanced Image Processing Techniques 1
- Image and Signal Denoising Methods 1
- Co-authors
- Eiichi Ohtsubo (1 shared paper)Nobuo Tsuchida (1 shared paper)Rui Mei (2 shared papers)Teresa Webster (2 shared papers)David Kulp (1 shared paper)Gang Lu (1 shared paper)Weimin Liu (1 shared paper)Paul Kaplan (1 shared paper)
- Journals
- Technology and Culture (1 paper)Science (1 paper)Proceedings of the National Academy of Sciences (1 paper)2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (1 paper)Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE (1 paper)
- Partner nations
- United StatesSweden
In The Last Decade
Tom Ryder
5 papers receiving 298 citations
Peers
Comparison fields: 5 of 63
- Molecular Biology 255
- Genetics 79
- Oncology 66
- Cancer Research 30
- Neurology 18
Countries citing papers authored by Tom Ryder
This map shows the geographic impact of Tom Ryder'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 Tom Ryder with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tom Ryder more than expected).
Fields of papers citing papers by Tom Ryder
This network shows the impact of papers produced by Tom Ryder. 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 Tom Ryder. The network helps show where Tom Ryder may publish in the future.
Co-authors
The 15 scholars most cited alongside Tom Ryder, 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 | 1982 | 212 | |
| 2 | 2003 | 103 | |
| 3 | 2001 | 12 | |
| 4 | 2022 | 6 | |
| 5 | 1980 | 2 | |
| 6 | Working with the Environment | 1996 | 1 |
About Tom Ryder
Tom Ryder is a scholar working on Molecular Biology, Computer Vision and Pattern Recognition, Oncology, Genetics and Immunology, having authored 6 papers that have together received 336 indexed citations. Recurring topics across this work include Gene expression and cancer classification (2 papers), Advanced biosensing and bioanalysis techniques (1 paper), Advanced Image Processing Techniques (1 paper), Molecular Biology Techniques and Applications (1 paper), Image and Signal Denoising Methods (1 paper), Advanced Biosensing Techniques and Applications (1 paper), Gene Regulatory Network Analysis (1 paper) and T-cell and Retrovirus Studies (1 paper). The work is most often cited by research in Molecular Biology (255 citations), Genetics (79 citations), Oncology (66 citations), Cancer Research (30 citations) and Neurology (18 citations). Tom Ryder has collaborated with scholars based in United States and Sweden. Frequent co-authors include Eiichi Ohtsubo, Nobuo Tsuchida, Rui Mei, Teresa Webster, David Kulp, Gang Lu, Weimin Liu, Paul Kaplan, Earl Hubbell and Stefan Bekiranov. Their work appears in journals such as Technology and Culture, Science, Proceedings of the National Academy of Sciences, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) and Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE.
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.