Rakesh Rawal
- Molecular Biology top 10%
- Cancer Research top 5%
- Oncology top 10%
- Computational Theory and Mathematics top 2%
- Plant Science top 10%
- Co-authors
- Dweipayan GoswamiPriyashi RaoPrabhudas S. PatelShanaya PatelKanisha ShahSheefa MirzaNayan JainBeena P. Patel
- Topics
- Computational Drug Discovery Methods (26 papers)MicroRNA in disease regulation (20 papers)Cancer-related molecular mechanisms research (12 papers)
- Journals
- SHILAP Revista de lepidopterologíaPLoS ONECancer Research
- Partner nations
- IndiaUnited StatesSouth Africa
In The Last Decade
Rakesh Rawal
184 papers receiving 2.3k citations
Peers
Comparison fields: 5 of 135
- Molecular Biology 1.1k
- Cancer Research 458
- Oncology 328
- Computational Theory and Mathematics 293
- Plant Science 250
Countries citing papers authored by Rakesh Rawal
This map shows the geographic impact of Rakesh Rawal'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 Rakesh Rawal with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rakesh Rawal more than expected).
Fields of papers citing papers by Rakesh Rawal
This network shows the impact of papers produced by Rakesh Rawal. 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 Rakesh Rawal. The network helps show where Rakesh Rawal may publish in the future.
Co-authorship network of co-authors of Rakesh Rawal
This figure shows the co-authorship network connecting the top 25 collaborators of Rakesh Rawal. A scholar is included among the top collaborators of Rakesh Rawal 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 Rakesh Rawal. Rakesh Rawal is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 0 | |
| 5 | 0 | |
| 6 | 17 | |
| 7 | 2 | |
| 8 | 0 | |
| 9 | 7 | |
| 10 | 5 | |
| 11 | 4 | |
| 12 | 0 | |
| 13 | 4 | |
| 14 | 8 | |
| 15 | 13 | |
| 16 | 6 | |
| 17 | 1 | |
| 18 | 34 | |
| 19 | A brief review on plant-derived natural compounds as an anti-cancer agents | 9 |
| 20 | STRUCTURAL AND FUNCTIONAL ANALYSIS OF AF9-MLL ONCOGENIC FUSION PROTEIN USING HOMOLOGY MODELING AND SIMULATION BASED APPROACH | 5 |
About Rakesh Rawal
Rakesh Rawal is a scholar working on Drug Discovery, Cancer Research and Applied Microbiology and Biotechnology, having authored 207 papers that have together received 2.4k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (26 papers), MicroRNA in disease regulation (20 papers) and Cancer-related molecular mechanisms research (12 papers). The work is most often cited by research in Cancer Research (458 citations), Computational Theory and Mathematics (293 citations) and Periodontics (79 citations). Rakesh Rawal has collaborated with scholars based in India, United States and South Africa. Frequent co-authors include Dweipayan Goswami, Priyashi Rao, Prabhudas S. Patel, Shanaya Patel, Kanisha Shah, Sheefa Mirza, Nayan Jain, Beena P. Patel, Meenu Saraf and Upendra M. Rawal. Their work appears in journals such as SHILAP Revista de lepidopterología, PLoS ONE and Cancer Research.
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.