Sanjeev Redkar
Impact in
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- Cancer Mechanisms and Therapy
- Hematology top 5%
- Acute Myeloid Leukemia Research
Papers in
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- Epigenetics and DNA Methylation 12
- Cancer-related gene regulation 4
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- Acute Myeloid Leukemia Research 4
- Co-authors
- Varsha Gandhi (4 shared papers)Lisa S. Chen (3 shared papers)David J. Bearss (7 shared papers)Pietro Taverna (10 shared papers)Peter A. Jones (2 shared papers)Christine B. Yoo (2 shared papers)William G. Wierda (2 shared papers)Jörge E. Cortes (1 shared paper)
- Journals
- Blood (8 papers)Molecular Cancer Therapeutics (5 papers)Cancer Chemotherapy and Pharmacology (4 papers)Cancer Research (4 papers)Journal of Hematology & Oncology (1 paper)
- Partner nations
- United StatesUnited KingdomNew Zealand
In The Last Decade
Sanjeev Redkar
28 papers receiving 1.0k citations
Peers
Comparison fields: 5 of 57
- Pathology and Forensic Medicine 363
- Hematology 187
- Molecular Biology 603
- Oncology 210
- Pharmaceutical Science 49
Countries citing papers authored by Sanjeev Redkar
This map shows the geographic impact of Sanjeev Redkar'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 Sanjeev Redkar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sanjeev Redkar more than expected).
Fields of papers citing papers by Sanjeev Redkar
This network shows the impact of papers produced by Sanjeev Redkar. 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 Sanjeev Redkar. The network helps show where Sanjeev Redkar may publish in the future.
Co-authors
The 25 scholars most cited alongside Sanjeev Redkar, 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 29 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2007 | 170 | |
| 2 | 2009 | 160 | |
| 3 | 2011 | 138 | |
| 4 | 2010 | 123 | |
| 5 | 2009 | 98 | |
| 6 | 2013 | 55 | |
| 7 | 2014 | 46 | |
| 8 | 2007 | 40 | |
| 9 | 2007 | 29 | |
| 10 | 2014 | 26 | |
| 11 | 2012 | 25 | |
| 12 | 2010 | 23 | |
| 13 | 2013 | 19 | |
| 14 | 2013 | 17 | |
| 15 | 2013 | 12 | |
| 16 | 2017 | 11 | |
| 17 | 2018 | 7 | |
| 18 | 2012 | 6 | |
| 19 | 2010 | 5 | |
| 20 | 2010 | 4 |
About Sanjeev Redkar
Sanjeev Redkar is a scholar working on Molecular Biology, Hematology, Genetics, Pathology and Forensic Medicine and Oncology, having authored 29 papers that have together received 1.0k indexed citations. Recurring topics across this work include Epigenetics and DNA Methylation (12 papers), Cancer-related gene regulation (4 papers), Cancer Mechanisms and Therapy (4 papers), Acute Myeloid Leukemia Research (4 papers), Hemoglobinopathies and Related Disorders (4 papers), Cancer Genomics and Diagnostics (2 papers), Liver physiology and pathology (2 papers) and Monoclonal and Polyclonal Antibodies Research (2 papers). The work is most often cited by research in Pathology and Forensic Medicine (363 citations), Hematology (187 citations), Molecular Biology (603 citations), Oncology (210 citations) and Pharmaceutical Science (49 citations). Sanjeev Redkar has collaborated with scholars based in United States, United Kingdom and New Zealand. Frequent co-authors include Varsha Gandhi, Lisa S. Chen, David J. Bearss, Pietro Taverna, Peter A. Jones, Christine B. Yoo, William G. Wierda, Jörge E. Cortes, Pasit Phiasivongsa and Chunlin Tang. Their work appears in journals such as Blood, Molecular Cancer Therapeutics, Cancer Chemotherapy and Pharmacology, Cancer Research and Journal of Hematology & Oncology.
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.