Deepika Mathur
Impact in
- Microbiology top 0.5%
- Antimicrobial Peptides and Activities
- Molecular Biology top 10%
- vaccines and immunoinformatics approaches
- Machine Learning in Bioinformatics
- Biochemical and Structural Characterization
- Protein Hydrolysis and Bioactive Peptides
- Chemical Synthesis and Analysis
- RNA and protein synthesis mechanisms
Papers in
-
- Chemical Synthesis and Analysis 5
- Biochemical and Structural Characterization 4
- vaccines and immunoinformatics approaches 4
- Machine Learning in Bioinformatics 2
-
- Antimicrobial Peptides and Activities 8
- Co-authors
- Gajendra P. S. Raghava (9 shared papers)Sandeep Singh (7 shared papers)Abhishek Tuknait (5 shared papers)Ankur Gautam (5 shared papers)Priya Anand (4 shared papers)Kumardeep Chaudhary (4 shared papers)Piyush Agrawal (3 shared papers)Grish C. Varshney (3 shared papers)
- Journals
- Nucleic Acids Research (3 papers)Scientific Reports (2 papers)PLoS ONE (2 papers)Clinical and Vaccine Immunology (1 paper)Nature Genetics (1 paper)
- Partner nations
- IndiaUnited StatesGermany
In The Last Decade
Deepika Mathur
15 papers receiving 1.2k citations
Peers
Comparison fields: 5 of 79
- Microbiology 542
- Molecular Biology 988
- Computational Theory and Mathematics 134
- Immunology 112
- Biotechnology 48
Countries citing papers authored by Deepika Mathur
This map shows the geographic impact of Deepika Mathur'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 Deepika Mathur with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Deepika Mathur more than expected).
Fields of papers citing papers by Deepika Mathur
This network shows the impact of papers produced by Deepika Mathur. 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 Deepika Mathur. The network helps show where Deepika Mathur may publish in the future.
Co-authors
The 25 scholars most cited alongside Deepika Mathur, 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 | 2014 | 313 | |
| 2 | 2016 | 189 | |
| 3 | 2015 | 181 | |
| 4 | 2013 | 130 | |
| 5 | 2016 | 128 | |
| 6 | 2018 | 92 | |
| 7 | 2014 | 76 | |
| 8 | 2010 | 33 | |
| 9 | 2023 | 22 | |
| 10 | 2010 | 22 | |
| 11 | 2021 | 21 | |
| 12 | 2013 | 14 | |
| 13 | 2018 | 12 | |
| 14 | 2023 | 9 | |
| 15 | 2007 | 3 | |
| 16 | 2025 | 0 |
About Deepika Mathur
Deepika Mathur is a scholar working on Molecular Biology, Microbiology, Immunology, Infectious Diseases and Surgery, having authored 16 papers that have together received 1.2k indexed citations. Recurring topics across this work include Antimicrobial Peptides and Activities (8 papers), Chemical Synthesis and Analysis (5 papers), Biochemical and Structural Characterization (4 papers), vaccines and immunoinformatics approaches (4 papers), Machine Learning in Bioinformatics (2 papers), Pancreatic function and diabetes (1 paper), Transgenic Plants and Applications (1 paper) and Supramolecular Self-Assembly in Materials (1 paper). The work is most often cited by research in Microbiology (542 citations), Molecular Biology (988 citations), Computational Theory and Mathematics (134 citations), Immunology (112 citations) and Biotechnology (48 citations). Deepika Mathur has collaborated with scholars based in India, United States and Germany. Frequent co-authors include Gajendra P. S. Raghava, Sandeep Singh, Abhishek Tuknait, Ankur Gautam, Priya Anand, Kumardeep Chaudhary, Piyush Agrawal, Grish C. Varshney, Minakshi Sharma and Atul Tyagi. Their work appears in journals such as Nucleic Acids Research, Scientific Reports, PLoS ONE, Clinical and Vaccine Immunology and Nature Genetics.
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.