Sumit Madan
Impact in
- Hematology top 5%
- Multiple Myeloma Research and Treatments
- Health Informatics top 10%
Papers in
-
- Biomedical Text Mining and Ontologies 17
- Bioinformatics and Genomic Networks 12
- Protein Degradation and Inhibitors 9
- Hematology 26
- Multiple Myeloma Research and Treatments 25
- Co-authors
- Shaji Kumar (8 shared papers)Martin Hofmann‐Apitius (12 shared papers)S. Vincent Rajkumar (6 shared papers)Angela Dispenzieri (7 shared papers)Morie A. Gertz (7 shared papers)Francis K. Buadi (7 shared papers)Martha Q. Lacy (7 shared papers)Suzanne R. Hayman (6 shared papers)
- Journals
- Blood (19 papers)Database (6 papers)Journal of Clinical Oncology (4 papers)Journal of Alzheimer s Disease (2 papers)Heliyon (2 papers)
- Partner nations
- United StatesGermanySpain
In The Last Decade
Sumit Madan
72 papers receiving 871 citations
Peers
Comparison fields: 5 of 119
- Hematology 216
- Health Informatics 15
- Oncology 221
- Genetics 80
- Molecular Biology 496
Countries citing papers authored by Sumit Madan
This map shows the geographic impact of Sumit Madan'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 Sumit Madan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sumit Madan more than expected).
Fields of papers citing papers by Sumit Madan
This network shows the impact of papers produced by Sumit Madan. 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 Sumit Madan. The network helps show where Sumit Madan may publish in the future.
Co-authors
The 25 scholars most cited alongside Sumit Madan, 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 74 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 1995 | 108 | |
| 2 | 2011 | 59 | |
| 3 | 2010 | 58 | |
| 4 | 2018 | 51 | |
| 5 | 2016 | 44 | |
| 6 | 2011 | 42 | |
| 7 | 2018 | 34 | |
| 8 | 2007 | 29 | |
| 9 | 2020 | 23 | |
| 10 | 2016 | 21 | |
| 11 | 2024 | 21 | |
| 12 | 2015 | 21 | |
| 13 | 2016 | 20 | |
| 14 | 2017 | 19 | |
| 15 | 2015 | 19 | |
| 16 | 2020 | 18 | |
| 17 | 2022 | 15 | |
| 18 | 2020 | 14 | |
| 19 | 2023 | 12 | |
| 20 | 2022 | 12 |
About Sumit Madan
Sumit Madan is a scholar working on Molecular Biology, Hematology, Oncology, Artificial Intelligence and Computational Theory and Mathematics, having authored 74 papers that have together received 906 indexed citations. Recurring topics across this work include Multiple Myeloma Research and Treatments (25 papers), Biomedical Text Mining and Ontologies (17 papers), Bioinformatics and Genomic Networks (12 papers), Protein Degradation and Inhibitors (9 papers), Computational Drug Discovery Methods (9 papers), Cancer Treatment and Pharmacology (8 papers), Monoclonal and Polyclonal Antibodies Research (6 papers) and Chronic Lymphocytic Leukemia Research (5 papers). The work is most often cited by research in Hematology (216 citations), Health Informatics (15 citations), Oncology (221 citations), Genetics (80 citations) and Molecular Biology (496 citations). Sumit Madan has collaborated with scholars based in United States, Germany and Spain. Frequent co-authors include Shaji Kumar, Martin Hofmann‐Apitius, S. Vincent Rajkumar, Angela Dispenzieri, Morie A. Gertz, Francis K. Buadi, Martha Q. Lacy, Suzanne R. Hayman, Juliane Fluck and Holger Fröhlich. Their work appears in journals such as Blood, Database, Journal of Clinical Oncology, Journal of Alzheimer s Disease and Heliyon.
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.