Subha Madhavan
Impact in
- Cancer Research top 1%
- Cancer Genomics and Diagnostics
- Cancer-related molecular mechanisms research
- MicroRNA in disease regulation
- Health Informatics top 2%
Papers in
-
- Cancer Genomics and Diagnostics 41
- Co-authors
- Howard A. FineYuriy GusevPeter B. McGarveyKenneth H. BuetowYuri KotliarovHimanso SahniMichael J. PishvaianKrithika Bhuvaneshwar
- Journals
- Journal of Clinical Oncology (8 papers)Oncotarget (7 papers)Cancer Research (5 papers)Journal of the American Medical Informatics Association (4 papers)PLoS ONE (4 papers)
- Partner nations
- United StatesBrazilUnited Kingdom
In The Last Decade
Subha Madhavan
108 papers receiving 3.1k citations
Hit Papers
Peers
Comparison fields: 5 of 146
- Cancer Research 1.2k
- Health Informatics 59
- Oncology 1.1k
- Genetics 272
- Molecular Biology 1.5k
Countries citing papers authored by Subha Madhavan
This map shows the geographic impact of Subha Madhavan'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 Subha Madhavan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Subha Madhavan more than expected).
Fields of papers citing papers by Subha Madhavan
This network shows the impact of papers produced by Subha Madhavan. 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 Subha Madhavan. The network helps show where Subha Madhavan may publish in the future.
Co-authors
The 25 scholars most cited alongside Subha Madhavan, 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 | 2025 | 8 | |
| 2 | 2022 | 3 | |
| 3 | 2022 | 6 | |
| 4 | 2021 | 16 | |
| 5 | 2020 | 7 | |
| 6 | Use of Electronic Health Records to Support a Public Health Response to the COVID-19 Pandemic in the United States: A Perspective from Fifteen Academic Medical Centers | 2020 | 1 |
| 7 | 2019 | 16 | |
| 8 | 2019 | 3 | |
| 9 | 2019 | 83 | |
| 10 | 2018 | 149 | |
| 11 | 2018 | 9 | |
| 12 | 2018 | 47 | |
| 13 | 2018 | 12 | |
| 14 | 2018 | 1 | |
| 15 | UD_GU_BioTM at TREC 2017: Precision Medicine Track. | 2017 | 2 |
| 16 | 2016 | 79 | |
| 17 | 2016 | 31 | |
| 18 | 2014 | 17 | |
| 19 | 2012 | 19 | |
| 20 | 2009 | 331 |
About Subha Madhavan
Subha Madhavan is a scholar working on Cancer Research, Health Informatics, Oncology, Information Systems and Management and Health Information Management, having authored 113 papers that have together received 3.2k indexed citations. Recurring topics across this work include Cancer Genomics and Diagnostics (41 papers), Bioinformatics and Genomic Networks (15 papers), Pancreatic and Hepatic Oncology Research (14 papers), Cancer Immunotherapy and Biomarkers (12 papers), Genomics and Rare Diseases (7 papers), Renal cell carcinoma treatment (7 papers), Computational Drug Discovery Methods (7 papers) and Colorectal Cancer Treatments and Studies (7 papers). The work is most often cited by research in Cancer Research (1.2k citations), Health Informatics (59 citations), Oncology (1.1k citations), Genetics (272 citations) and Molecular Biology (1.5k citations). Subha Madhavan has collaborated with scholars based in United States, Brazil and United Kingdom. Frequent co-authors include Howard A. Fine, Yuriy Gusev, Peter B. McGarvey, Kenneth H. Buetow, Yuri Kotliarov, Himanso Sahni, Michael J. Pishvaian, Krithika Bhuvaneshwar, Jonathan R. Brody and Andrew Hendifar. Their work appears in journals such as Journal of Clinical Oncology, Oncotarget, Cancer Research, Journal of the American Medical Informatics Association and PLoS ONE.
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.