Jagat Chauhan
- Molecular Biology top 10%
- Machine Learning in Bioinformatics 8
- Genomics and Phylogenetic Studies 5
- Melanoma and MAPK Pathways 5
- Glycosylation and Glycoproteins Research 4
- Epigenetics and DNA Methylation 3
- Protein Hydrolysis and Bioactive Peptides 3
- RNA and protein synthesis mechanisms 3
- Microbiology top 5%
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- Computational Drug Discovery Methods 6
- Cell Biology top 10%
- Co-authors
- Gajendra P. S. RaghavaAlka RaoNitish K. MishraKumardeep ChaudharyRavi KumarColin R. GodingGandharva NagpalMinakshi Sharma
- Journals
- Nucleic Acids Research (3 papers)Genes & Development (4 papers)SHILAP Revista de lepidopterología (1 paper)
- Partner nations
- United KingdomIndiaUnited States
In The Last Decade
Jagat Chauhan
30 papers receiving 1.5k citations
Peers
Comparison fields: 5 of 96
- Molecular Biology 1.2k
- Microbiology 90
- Computational Theory and Mathematics 201
- Cancer Research 145
- Cell Biology 145
Countries citing papers authored by Jagat Chauhan
This map shows the geographic impact of Jagat Chauhan'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 Jagat Chauhan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jagat Chauhan more than expected).
Fields of papers citing papers by Jagat Chauhan
This network shows the impact of papers produced by Jagat Chauhan. 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 Jagat Chauhan. The network helps show where Jagat Chauhan may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Jagat Chauhan, 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 | 2023 | 14 | |
| 2 | 2021 | 7 | |
| 3 | 2021 | 5 | |
| 4 | 2021 | 12 | |
| 5 | 2020 | 20 | |
| 6 | 2019 | 25 | |
| 7 | 2019 | 91 | |
| 8 | 2019 | 42 | |
| 9 | 2017 | 69 | |
| 10 | 2017 | 156 | |
| 11 | 2016 | 77 | |
| 12 | 2015 | 144 | |
| 13 | 2014 | 171 | |
| 14 | 2014 | 33 | |
| 15 | 2013 | 177 | |
| 16 | 2013 | 18 | |
| 17 | 2013 | 69 | |
| 18 | 2011 | 20 | |
| 19 | 2011 | 25 | |
| 20 | 2009 | 117 |
About Jagat Chauhan
Jagat Chauhan is a scholar working on Computational Theory and Mathematics, Molecular Biology and Immunology and Allergy, having authored 31 papers that have together received 1.5k indexed citations. Recurring topics across this work include Machine Learning in Bioinformatics (8 papers), Computational Drug Discovery Methods (6 papers), Genomics and Phylogenetic Studies (5 papers), Melanoma and MAPK Pathways (5 papers), Glycosylation and Glycoproteins Research (4 papers), Epigenetics and DNA Methylation (3 papers), Protein Hydrolysis and Bioactive Peptides (3 papers) and RNA and protein synthesis mechanisms (3 papers). The work is most often cited by research in Molecular Biology (1.2k citations), Microbiology (90 citations) and Computational Theory and Mathematics (201 citations). Jagat Chauhan has collaborated with scholars based in United Kingdom, India and United States. Frequent co-authors include Gajendra P. S. Raghava, Alka Rao, Nitish K. Mishra, Kumardeep Chaudhary, Ravi Kumar, Colin R. Goding, Gandharva Nagpal, Minakshi Sharma, Ankur Gautam and Rahul Kumar. Their work appears in journals such as Nucleic Acids Research, Genes & Development and SHILAP Revista de lepidopterología.
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.