Ram Samudrala
Impact in
- Endocrinology top 2%
- Computational Theory and Mathematics top 0.5%
- Computational Drug Discovery Methods
Papers in
-
- Protein Structure and Dynamics 40
- RNA and protein synthesis mechanisms 25
- Machine Learning in Bioinformatics 17
- Bioinformatics and Genomic Networks 17
-
- Computational Drug Discovery Methods 25
- Co-authors
- John Moult (6 shared papers)Ekachai Jenwitheesuk (12 shared papers)Enoch S. Huang (9 shared papers)Michael Levitt (8 shared papers)Jason McDermott (13 shared papers)Aaron D. Goldman (4 shared papers)Michael D. Levitt (1 shared paper)Kai Wang (8 shared papers)
- Journals
- Proteins Structure Function and Bioinformatics (8 papers)Bioinformatics (5 papers)Molecules (5 papers)Journal of Molecular Biology (4 papers)Antiviral Therapy (4 papers)
- Partner nations
- United StatesThailandChina
In The Last Decade
Ram Samudrala
127 papers receiving 4.7k citations
Peers
Comparison fields: 5 of 164
- Endocrinology 256
- Computational Theory and Mathematics 780
- Molecular Biology 3.0k
- Periodontics 156
- Virology 159
Countries citing papers authored by Ram Samudrala
This map shows the geographic impact of Ram Samudrala'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 Ram Samudrala with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ram Samudrala more than expected).
Fields of papers citing papers by Ram Samudrala
This network shows the impact of papers produced by Ram Samudrala. 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 Ram Samudrala. The network helps show where Ram Samudrala may publish in the future.
Co-authors
The 25 scholars most cited alongside Ram Samudrala, 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 129 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2010 | 404 | |
| 2 | 1998 | 367 | |
| 3 | 2000 | 168 | |
| 4 | 2009 | 156 | |
| 5 | 2004 | 143 | |
| 6 | 2000 | 134 | |
| 7 | 2002 | 127 | |
| 8 | 2007 | 117 | |
| 9 | 1998 | 105 | |
| 10 | 2007 | 103 | |
| 11 | 2023 | 96 | |
| 12 | 2011 | 93 | |
| 13 | 2010 | 91 | |
| 14 | 2008 | 89 | |
| 15 | 2005 | 87 | |
| 16 | 2010 | 87 | |
| 17 | 2006 | 77 | |
| 18 | 1999 | 72 | |
| 19 | 2010 | 68 | |
| 20 | 2005 | 67 |
About Ram Samudrala
Ram Samudrala is a scholar working on Molecular Biology, Computational Theory and Mathematics, Materials Chemistry, Infectious Diseases and Virology, having authored 129 papers that have together received 4.8k indexed citations. Recurring topics across this work include Protein Structure and Dynamics (40 papers), Computational Drug Discovery Methods (25 papers), RNA and protein synthesis mechanisms (25 papers), Enzyme Structure and Function (20 papers), Machine Learning in Bioinformatics (17 papers), Bioinformatics and Genomic Networks (17 papers), HIV Research and Treatment (10 papers) and HIV/AIDS drug development and treatment (9 papers). The work is most often cited by research in Endocrinology (256 citations), Computational Theory and Mathematics (780 citations), Molecular Biology (3.0k citations), Periodontics (156 citations) and Virology (159 citations). Ram Samudrala has collaborated with scholars based in United States, Thailand and China. Frequent co-authors include John Moult, Ekachai Jenwitheesuk, Enoch S. Huang, Michael Levitt, Jason McDermott, Aaron D. Goldman, Michael D. Levitt, Kai Wang, Yu Xia and Keiji Murakami. Their work appears in journals such as Proteins Structure Function and Bioinformatics, Bioinformatics, Molecules, Journal of Molecular Biology and Antiviral Therapy.
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.