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 3
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- Acute Myeloid Leukemia Research 3
- Co-authors
- Varsha Gandhi (4 shared papers)Lisa S. Chen (3 shared papers)David J. Bearss (6 shared papers)Pietro Taverna (10 shared papers)Christine B. Yoo (2 shared papers)Peter A. Jones (2 shared papers)William G. Wierda (2 shared papers)Jörge E. Cortes (1 shared paper)
- Journals
- Blood (8 papers)Molecular Cancer Therapeutics (4 papers)Cancer Chemotherapy and Pharmacology (4 papers)Cancer Research (4 papers)Clinical Cancer Research (1 paper)
- Partner nations
- United StatesUnited KingdomIndia
In The Last Decade
Sanjeev Redkar
29 papers receiving 993 citations
Peers
Comparison fields: 5 of 59
- Pathology and Forensic Medicine 368
- Hematology 197
- Molecular Biology 673
- Oncology 251
- Pharmaceutical Science 50
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 | 167 | |
| 2 | 2009 | 160 | |
| 3 | 2011 | 135 | |
| 4 | 2010 | 120 | |
| 5 | 2009 | 98 | |
| 6 | 2013 | 54 | |
| 7 | 2014 | 45 | |
| 8 | 2007 | 38 | |
| 9 | 2007 | 28 | |
| 10 | 2014 | 25 | |
| 11 | 2012 | 25 | |
| 12 | 2010 | 23 | |
| 13 | 2013 | 19 | |
| 14 | 2013 | 16 | |
| 15 | 2013 | 11 | |
| 16 | 2017 | 11 | |
| 17 | 2018 | 7 | |
| 18 | 2012 | 6 | |
| 19 | 2010 | 5 | |
| 20 | 2025 | 4 |
About Sanjeev Redkar
Sanjeev Redkar is a scholar working on Molecular Biology, Hematology, Genetics, Oncology and Pathology and Forensic Medicine, 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 Mechanisms and Therapy (5 papers), Hemoglobinopathies and Related Disorders (4 papers), Acute Myeloid Leukemia Research (3 papers), Prenatal Screening and Diagnostics (3 papers), Cancer Genomics and Diagnostics (3 papers), Cancer-related gene regulation (3 papers) and Monoclonal and Polyclonal Antibodies Research (3 papers). The work is most often cited by research in Pathology and Forensic Medicine (368 citations), Hematology (197 citations), Molecular Biology (673 citations), Oncology (251 citations) and Pharmaceutical Science (50 citations). Sanjeev Redkar has collaborated with scholars based in United States, United Kingdom and India. Frequent co-authors include Varsha Gandhi, Lisa S. Chen, David J. Bearss, Pietro Taverna, Christine B. Yoo, Peter A. Jones, William G. Wierda, Jörge E. Cortes, Chunlin Tang and Pasit Phiasivongsa. Their work appears in journals such as Blood, Molecular Cancer Therapeutics, Cancer Chemotherapy and Pharmacology, Cancer Research and Clinical Cancer Research.
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.