Valadi K. Jayaraman
- Molecular Biology
- Microbiology top 5%
- Biomedical Engineering
- Mechanical Engineering
- Computational Theory and Mathematics top 10%
- Co-authors
- Bhaskar D. KulkarniSusan Idicula‐ThomasShreyas KarnikPiyushkumar A. MundraJyeshtharaj B. JoshiAbhijit KulkarniPetety V. BalajiRamanathan Natarajan
- Topics
- Machine Learning in Bioinformatics (10 papers)Protein Structure and Dynamics (5 papers)Computational Drug Discovery Methods (4 papers)
- Partner nations
- IndiaCanadaUnited States
In The Last Decade
Valadi K. Jayaraman
24 papers receiving 534 citations
Peers
Comparison fields: 5 of 97
- Molecular Biology 335
- Microbiology 123
- Biomedical Engineering 87
- Mechanical Engineering 50
- Computational Theory and Mathematics 49
Countries citing papers authored by Valadi K. Jayaraman
This map shows the geographic impact of Valadi K. Jayaraman'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 Valadi K. Jayaraman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Valadi K. Jayaraman more than expected).
Fields of papers citing papers by Valadi K. Jayaraman
This network shows the impact of papers produced by Valadi K. Jayaraman. 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 Valadi K. Jayaraman. The network helps show where Valadi K. Jayaraman may publish in the future.
Co-authorship network of co-authors of Valadi K. Jayaraman
This figure shows the co-authorship network connecting the top 25 collaborators of Valadi K. Jayaraman. A scholar is included among the top collaborators of Valadi K. Jayaraman based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Valadi K. Jayaraman. Valadi K. Jayaraman is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 5 | |
| 2 | 7 | |
| 3 | 26 | |
| 4 | 10 | |
| 5 | 4 | |
| 6 | 3 | |
| 7 | 3 | |
| 8 | 126 | |
| 9 | 1 | |
| 10 | 25 | |
| 11 | 5 | |
| 12 | 11 | |
| 13 | 23 | |
| 14 | 27 | |
| 15 | 6 | |
| 16 | 24 | |
| 17 | 88 | |
| 18 | An ant colony optimization-based classifier system for bacterial growth | 1 |
| 19 | 1 | |
| 20 | 0 |
About Valadi K. Jayaraman
Valadi K. Jayaraman is a scholar working on Computational Theory and Mathematics, Water Science and Technology and Molecular Biology, having authored 25 papers that have together received 556 indexed citations. Recurring topics across this work include Machine Learning in Bioinformatics (10 papers), Protein Structure and Dynamics (5 papers) and Computational Drug Discovery Methods (4 papers). The work is most often cited by research in Microbiology (123 citations), Molecular Biology (335 citations) and Computational Theory and Mathematics (49 citations). Valadi K. Jayaraman has collaborated with scholars based in India, Canada and United States. Frequent co-authors include Bhaskar D. Kulkarni, Susan Idicula‐Thomas, Shreyas Karnik, Piyushkumar A. Mundra, Jyeshtharaj B. Joshi, Abhijit Kulkarni, Petety V. Balaji, Ramanathan Natarajan, Urmila Kulkarni‐Kale and Shamel S. Merchant. Their work appears in journals such as Bioinformatics, Industrial & Engineering Chemistry Research and Chemical Engineering Science.
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.