Debyani Chakravarty
- Molecular Biology top 10%
- Cancer Research top 2%
- Oncology top 5%
- Pulmonary and Respiratory Medicine top 5%
- Pathology and Forensic Medicine top 5%
- Co-authors
- David B. SolitAlicia PedrazaNikolaus SchultzCameron BrennanUsha N. KasidTatsuya OzawaMargaret LevershaTom Mikkelsen
- Topics
- Cancer Genomics and Diagnostics (22 papers)Genetic factors in colorectal cancer (7 papers)Radiomics and Machine Learning in Medical Imaging (4 papers)
- Cited by
- Cancer ResearchGeneticsOncology
- Journals
- Proceedings of the National Academy of SciencesJournal of Clinical InvestigationNature Communications
- Partner nations
- United StatesUnited KingdomSwitzerland
In The Last Decade
Debyani Chakravarty
31 papers receiving 1.9k citations
Hit Papers
Peers
Comparison fields: 5 of 90
- Molecular Biology 856
- Cancer Research 776
- Oncology 602
- Pulmonary and Respiratory Medicine 411
- Pathology and Forensic Medicine 266
Countries citing papers authored by Debyani Chakravarty
This map shows the geographic impact of Debyani Chakravarty'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 Debyani Chakravarty with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Debyani Chakravarty more than expected).
Fields of papers citing papers by Debyani Chakravarty
This network shows the impact of papers produced by Debyani Chakravarty. 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 Debyani Chakravarty. The network helps show where Debyani Chakravarty may publish in the future.
Co-authorship network of co-authors of Debyani Chakravarty
This figure shows the co-authorship network connecting the top 25 collaborators of Debyani Chakravarty. A scholar is included among the top collaborators of Debyani Chakravarty based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Debyani Chakravarty. Debyani Chakravarty is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 3 | |
| 4 | 3 | |
| 5 | 1 | |
| 6 | 0 | |
| 7 | 3 | |
| 8 | 19 | |
| 9 | 18 | |
| 10 | 26 | |
| 11 | 6 | |
| 12 | 104 | |
| 13 | 7 | |
| 14 | 98 | |
| 15 | A framework to rank genomic alterations as targets for cancer precision medicine: the ESMO Scale for Clinical Actionability of molecular Targets (ESCAT)breakdown → | 391 |
| 16 | 73 | |
| 17 | 32 | |
| 18 | 286 | |
| 19 | 83 | |
| 20 | 136 |
About Debyani Chakravarty
Debyani Chakravarty is a scholar working on Cancer Research, Pathology and Forensic Medicine and Immunology and Allergy, having authored 35 papers that have together received 1.9k indexed citations. Recurring topics across this work include Cancer Genomics and Diagnostics (22 papers), Genetic factors in colorectal cancer (7 papers) and Radiomics and Machine Learning in Medical Imaging (4 papers). The work is most often cited by research in Cancer Research (776 citations), Genetics (264 citations) and Oncology (602 citations). Debyani Chakravarty has collaborated with scholars based in United States, United Kingdom and Switzerland. Frequent co-authors include David B. Solit, Alicia Pedraza, Nikolaus Schultz, Cameron Brennan, Usha N. Kasid, Tatsuya Ozawa, Margaret Leversha, Tom Mikkelsen, Imran Ahmad and Yuqiang Fang. Their work appears in journals such as Proceedings of the National Academy of Sciences, Journal of Clinical Investigation and Nature Communications.
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.