Rahul Kumar
Impact in
- Microbiology top 0.5%
- Antimicrobial Peptides and Activities
- Molecular Biology top 2%
- vaccines and immunoinformatics approaches
- Protein Hydrolysis and Bioactive Peptides
- Machine Learning in Bioinformatics
- RNA Interference and Gene Delivery
Papers in
-
- RNA Interference and Gene Delivery 7
- Machine Learning in Bioinformatics 7
- Advanced biosensing and bioanalysis techniques 5
- vaccines and immunoinformatics approaches 5
- Oncology 16
- Co-authors
- Gajendra P. S. Raghava (21 shared papers)Kumardeep Chaudhary (17 shared papers)Pallavi Kapoor (10 shared papers)Ankur Gautam (13 shared papers)Sudheer Gupta (7 shared papers)Atul Tyagi (4 shared papers)Harinder Singh (5 shared papers)Arun Sharma (2 shared papers)
- Journals
- Scientific Reports (9 papers)Gynecologic Oncology (3 papers)PLoS ONE (3 papers)eLife (2 papers)Database (2 papers)
- Partner nations
- IndiaUnited StatesSwitzerland
In The Last Decade
Rahul Kumar
57 papers receiving 3.8k citations
Rahul Kumar's Hit Papers
Peers
Comparison fields: 5 of 111
- Microbiology 678
- Molecular Biology 3.0k
- Biotechnology 253
- Immunology 539
- Computational Theory and Mathematics 358
Countries citing papers authored by Rahul Kumar
This map shows the geographic impact of Rahul Kumar'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 Rahul Kumar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rahul Kumar more than expected).
Fields of papers citing papers by Rahul Kumar
This network shows the impact of papers produced by Rahul Kumar. 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 Rahul Kumar. The network helps show where Rahul Kumar may publish in the future.
Co-authors
The 25 scholars most cited alongside Rahul Kumar, 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 60 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | In Silico Approach for Predicting Toxicity of Peptides and Proteins Hit paper breakdown → | 2013 | 1409 |
| 2 | 2013 | 258 | |
| 3 | 2013 | 248 | |
| 4 | 2014 | 172 | |
| 5 | 2012 | 165 | |
| 6 | 2015 | 144 | |
| 7 | 2020 | 115 | |
| 8 | 2012 | 114 | |
| 9 | 2013 | 94 | |
| 10 | 2022 | 74 | |
| 11 | 2014 | 74 | |
| 12 | 2013 | 69 | |
| 13 | 2015 | 67 | |
| 14 | 2017 | 64 | |
| 15 | 2017 | 64 | |
| 16 | 2018 | 61 | |
| 17 | 2021 | 53 | |
| 18 | 2017 | 47 | |
| 19 | 2016 | 46 | |
| 20 | 2014 | 42 |
About Rahul Kumar
Rahul Kumar is a scholar working on Molecular Biology, Oncology, Cancer Research, Pathology and Forensic Medicine and Computational Theory and Mathematics, having authored 60 papers that have together received 3.8k indexed citations. Recurring topics across this work include Cancer Genomics and Diagnostics (11 papers), Computational Drug Discovery Methods (9 papers), RNA Interference and Gene Delivery (7 papers), Machine Learning in Bioinformatics (7 papers), Antimicrobial Peptides and Activities (5 papers), Advanced biosensing and bioanalysis techniques (5 papers), vaccines and immunoinformatics approaches (5 papers) and Lymphoma Diagnosis and Treatment (4 papers). The work is most often cited by research in Microbiology (678 citations), Molecular Biology (3.0k citations), Biotechnology (253 citations), Immunology (539 citations) and Computational Theory and Mathematics (358 citations). Rahul Kumar has collaborated with scholars based in India, United States and Switzerland. Frequent co-authors include Gajendra P. S. Raghava, Kumardeep Chaudhary, Pallavi Kapoor, Ankur Gautam, Sudheer Gupta, Atul Tyagi, Harinder Singh, Arun Sharma, Jagat Chauhan and Minakshi Sharma. Their work appears in journals such as Scientific Reports, Gynecologic Oncology, PLoS ONE, eLife and Database.
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.