Kalidas Yeturu
Impact in
-
- Computational Drug Discovery Methods
- Infectious Diseases top 10%
- Tuberculosis Research and Epidemiology
Papers in
-
- Protein Structure and Dynamics 5
- RNA and protein synthesis mechanisms 4
- Machine Learning in Bioinformatics 2
- Genetics, Bioinformatics, and Biomedical Research 1
-
- Computational Drug Discovery Methods 3
- Co-authors
- Nagasuma Chandra (8 shared papers)Karthik Raman (1 shared paper)Praveen Anand (3 shared papers)Samir K. Brahmachari (1 shared paper)Roman A. Laskowski (1 shared paper)Anshu Bhardwaj (1 shared paper)Sankaran Sandhya (1 shared paper)Sumanta Mukherjee (1 shared paper)
- Journals
- BMC Bioinformatics (2 papers)Journal of Structural Biology (1 paper)BMC Systems Biology (1 paper)Nucleic Acids Research (1 paper)Journal of Chemical Information and Modeling (1 paper)
- Partner nations
- IndiaUnited KingdomSweden
In The Last Decade
Kalidas Yeturu
10 papers receiving 477 citations
Peers
Comparison fields: 5 of 58
- Computational Theory and Mathematics 219
- Infectious Diseases 148
- Molecular Biology 399
- Molecular Medicine 13
- Pharmacology 35
Countries citing papers authored by Kalidas Yeturu
This map shows the geographic impact of Kalidas Yeturu'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 Kalidas Yeturu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kalidas Yeturu more than expected).
Fields of papers citing papers by Kalidas Yeturu
This network shows the impact of papers produced by Kalidas Yeturu. 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 Kalidas Yeturu. The network helps show where Kalidas Yeturu may publish in the future.
Co-authors
The 9 scholars most cited alongside Kalidas Yeturu, 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 | 2008 | 194 | |
| 2 | 2008 | 121 | |
| 3 | 2007 | 76 | |
| 4 | 2011 | 33 | |
| 5 | 2011 | 30 | |
| 6 | 2012 | 16 | |
| 7 | 2010 | 7 | |
| 8 | 2010 | 2 | |
| 9 | 2022 | 2 | |
| 10 | 2013 | 1 |
About Kalidas Yeturu
Kalidas Yeturu is a scholar working on Molecular Biology, Computational Theory and Mathematics, Materials Chemistry, Infectious Diseases and Computer Vision and Pattern Recognition, having authored 10 papers that have together received 482 indexed citations. Recurring topics across this work include Protein Structure and Dynamics (5 papers), RNA and protein synthesis mechanisms (4 papers), Computational Drug Discovery Methods (3 papers), Enzyme Structure and Function (3 papers), Machine Learning in Bioinformatics (2 papers), Tuberculosis Research and Epidemiology (2 papers), Genetics, Bioinformatics, and Biomedical Research (1 paper) and Video Surveillance and Tracking Methods (1 paper). The work is most often cited by research in Computational Theory and Mathematics (219 citations), Infectious Diseases (148 citations), Molecular Biology (399 citations), Molecular Medicine (13 citations) and Pharmacology (35 citations). Kalidas Yeturu has collaborated with scholars based in India, United Kingdom and Sweden. Frequent co-authors include Nagasuma Chandra, Karthik Raman, Praveen Anand, Samir K. Brahmachari, Roman A. Laskowski, Anshu Bhardwaj, Sankaran Sandhya, Sumanta Mukherjee and Sibsambhu Kar. Their work appears in journals such as BMC Bioinformatics, Journal of Structural Biology, BMC Systems Biology, Nucleic Acids Research and Journal of Chemical Information and Modeling.
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.