Tane S. Ray
Impact in
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- Lymphoma Diagnosis and Treatment
- Genetics top 5%
- Chronic Lymphocytic Leukemia Research
Papers in
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- Theoretical and Computational Physics 16
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- Stochastic processes and statistical mechanics 9
- Co-authors
- Pablo Tamayo (4 shared papers)Ricardo C.T. Aguiar (1 shared paper)T. Andrew Lister (1 shared paper)Kim Last (1 shared paper)Ken N. Ross (1 shared paper)Andrew P. Weng (1 shared paper)Todd R. Golub (1 shared paper)Geraldine S. Pinkus (1 shared paper)
- Journals
- Journal of Statistical Physics (7 papers)Physical Review A (3 papers)International Journal of Modern Physics C (3 papers)Physical Review Letters (3 papers)Theory in Biosciences (2 papers)
- Partner nations
- United StatesCanadaBarbados
In The Last Decade
Tane S. Ray
30 papers receiving 2.2k citations
Tane S. Ray's Hit Papers
Peers
Comparison fields: 5 of 142
- Pathology and Forensic Medicine 543
- Genetics 230
- Molecular Biology 1.0k
- Condensed Matter Physics 174
- Oncology 299
Countries citing papers authored by Tane S. Ray
This map shows the geographic impact of Tane S. Ray'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 Tane S. Ray with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tane S. Ray more than expected).
Fields of papers citing papers by Tane S. Ray
This network shows the impact of papers produced by Tane S. Ray. 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 Tane S. Ray. The network helps show where Tane S. Ray may publish in the future.
Co-authors
The 25 scholars most cited alongside Tane S. Ray, 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 | Diffuse large B-cell lymphoma outcome prediction by gene-expression profiling and supervised machine learning Hit paper breakdown → | 2002 | 1855 |
| 2 | 1994 | 47 | |
| 3 | 2008 | 44 | |
| 4 | 2017 | 36 | |
| 5 | 1989 | 34 | |
| 6 | 1989 | 28 | |
| 7 | 1990 | 20 | |
| 8 | 1982 | 19 | |
| 9 | 1990 | 18 | |
| 10 | 1988 | 17 | |
| 11 | 1992 | 17 | |
| 12 | 1999 | 11 | |
| 13 | 1998 | 11 | |
| 14 | 1994 | 9 | |
| 15 | 1983 | 9 | |
| 16 | 1993 | 9 | |
| 17 | 1991 | 8 | |
| 18 | 1994 | 8 | |
| 19 | 1999 | 7 | |
| 20 | 1992 | 6 |
About Tane S. Ray
Tane S. Ray is a scholar working on Condensed Matter Physics, Mathematical Physics, Molecular Biology, Statistical and Nonlinear Physics and Atomic and Molecular Physics, and Optics, having authored 31 papers that have together received 2.2k indexed citations. Recurring topics across this work include Theoretical and Computational Physics (16 papers), Stochastic processes and statistical mechanics (9 papers), Evolution and Genetic Dynamics (4 papers), Complex Systems and Time Series Analysis (4 papers), Random lasers and scattering media (3 papers), Evolutionary Game Theory and Cooperation (3 papers), Material Dynamics and Properties (3 papers) and Quantum many-body systems (2 papers). The work is most often cited by research in Pathology and Forensic Medicine (543 citations), Genetics (230 citations), Molecular Biology (1.0k citations), Condensed Matter Physics (174 citations) and Oncology (299 citations). Tane S. Ray has collaborated with scholars based in United States, Canada and Barbados. Frequent co-authors include Pablo Tamayo, Ricardo C.T. Aguiar, T. Andrew Lister, Kim Last, Ken N. Ross, Andrew P. Weng, Todd R. Golub, Geraldine S. Pinkus, Jeffery L. Kutok and Michelle Gaasenbeek. Their work appears in journals such as Journal of Statistical Physics, Physical Review A, International Journal of Modern Physics C, Physical Review Letters and Theory in Biosciences.
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.