Tapsi Kumar
Impact in
- Cancer Research top 10%
- Cancer Genomics and Diagnostics
- Cancer-related molecular mechanisms research
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- Cancer Immunotherapy and Biomarkers
- Cancer Cells and Metastasis
- Pancreatic and Hepatic Oncology Research
Papers in
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- Cancer Genomics and Diagnostics 3
- Breast Cancer Treatment Studies 2
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- Single-cell and spatial transcriptomics 2
- Gene expression and cancer classification 1
- Co-authors
- Nicholas E. Navin (3 shared papers)Ken Chen (2 shared papers)Fang Wang (2 shared papers)Shanshan Bai (2 shared papers)Min Hu (2 shared papers)Aislyn Schalck (2 shared papers)Emi Sei (2 shared papers)Ying C. Henderson (1 shared paper)
- Journals
- Journal of Clinical Oncology (1 paper)Clinical Cancer Research (1 paper)PLoS Computational Biology (1 paper)Cancer Discovery (1 paper)Microsystem Technologies (1 paper)
- Partner nations
- United StatesIndiaUnited Kingdom
In The Last Decade
Tapsi Kumar
8 papers receiving 548 citations
Tapsi Kumar's Hit Papers
Peers
Comparison fields: 5 of 47
- Cancer Research 190
- Oncology 143
- Immunology 98
- Molecular Biology 318
- Biophysics 17
Countries citing papers authored by Tapsi Kumar
This map shows the geographic impact of Tapsi Kumar'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 Tapsi Kumar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tapsi Kumar more than expected).
Fields of papers citing papers by Tapsi Kumar
This network shows the impact of papers produced by Tapsi Kumar. 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 Tapsi Kumar. The network helps show where Tapsi Kumar may publish in the future.
Co-authors
The 25 scholars most cited alongside Tapsi Kumar, 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 | Delineating copy number and clonal substructure in human tumors from single-cell transcriptomes Hit paper breakdown → | 2021 | 468 |
| 2 | 2022 | 45 | |
| 3 | 2019 | 23 | |
| 4 | 2022 | 8 | |
| 5 | 1992 | 4 | |
| 6 | 2020 | 3 | |
| 7 | 2025 | 1 | |
| 8 | 2019 | 1 |
About Tapsi Kumar
Tapsi Kumar is a scholar working on Cancer Research, Molecular Biology, Oncology, Pathology and Forensic Medicine and Genetics, having authored 8 papers that have together received 553 indexed citations. Recurring topics across this work include Cancer Genomics and Diagnostics (3 papers), Breast Cancer Treatment Studies (2 papers), Single-cell and spatial transcriptomics (2 papers), Terahertz technology and applications (1 paper), Plasmonic and Surface Plasmon Research (1 paper), Cancer Immunotherapy and Biomarkers (1 paper), Pancreatic and Hepatic Oncology Research (1 paper) and Gene expression and cancer classification (1 paper). The work is most often cited by research in Cancer Research (190 citations), Oncology (143 citations), Immunology (98 citations), Molecular Biology (318 citations) and Biophysics (17 citations). Tapsi Kumar has collaborated with scholars based in United States, India and United Kingdom. Frequent co-authors include Nicholas E. Navin, Ken Chen, Fang Wang, Shanshan Bai, Min Hu, Aislyn Schalck, Emi Sei, Ying C. Henderson, Simona F. Shaitelman and Alexander Davis. Their work appears in journals such as Journal of Clinical Oncology, Clinical Cancer Research, PLoS Computational Biology, Cancer Discovery and Microsystem Technologies.
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.