Nitin Kumar
Impact in
- Molecular Medicine top 5%
- Antibiotic Resistance in Bacteria
- Endocrinology top 10%
- Escherichia coli research studies
Papers in
-
- Tuberculosis Research and Epidemiology 4
- Amoebic Infections and Treatments 2
-
- Antibiotic Resistance in Bacteria 5
- Co-authors
- Chih‐Chia Su (12 shared papers)Edward Yu (12 shared papers)Kanagalaghatta R. Rajashankar (11 shared papers)Abhijith Radhakrishnan (12 shared papers)Jani Reddy Bolla (10 shared papers)Jared A. Delmar (9 shared papers)Tsung‐Han Chou (8 shared papers)Feng Long (5 shared papers)
- Journals
- Protein Science (4 papers)PLoS ONE (2 papers)Journal of Biological Chemistry (2 papers)Nature Communications (2 papers)Proceedings of the National Academy of Sciences (1 paper)
- Partner nations
- United States
In The Last Decade
Nitin Kumar
13 papers receiving 470 citations
Peers
Comparison fields: 5 of 76
- Molecular Medicine 164
- Endocrinology 48
- Infectious Diseases 161
- Microbiology 48
- Genetics 113
Countries citing papers authored by Nitin Kumar
This map shows the geographic impact of Nitin 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 Nitin Kumar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nitin Kumar more than expected).
Fields of papers citing papers by Nitin Kumar
This network shows the impact of papers produced by Nitin 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 Nitin Kumar. The network helps show where Nitin Kumar may publish in the future.
Co-authors
The 18 scholars most cited alongside Nitin 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
| # | Work | ||
|---|---|---|---|
| 1 | 2017 | 70 | |
| 2 | 2014 | 69 | |
| 3 | 2014 | 58 | |
| 4 | 2014 | 57 | |
| 5 | 2015 | 42 | |
| 6 | 2017 | 42 | |
| 7 | 2015 | 36 | |
| 8 | 2015 | 29 | |
| 9 | 2014 | 24 | |
| 10 | 2014 | 23 | |
| 11 | 2015 | 13 | |
| 12 | 2014 | 5 | |
| 13 | 2015 | 4 |
About Nitin Kumar
Nitin Kumar is a scholar working on Infectious Diseases, Molecular Medicine, Molecular Biology, Epidemiology and Microbiology, having authored 13 papers that have together received 472 indexed citations. Recurring topics across this work include Antibiotic Resistance in Bacteria (5 papers), Tuberculosis Research and Epidemiology (4 papers), Bacterial Infections and Vaccines (4 papers), Mycobacterium research and diagnosis (4 papers), Bacterial Genetics and Biotechnology (2 papers), Salmonella and Campylobacter epidemiology (2 papers), Drug Transport and Resistance Mechanisms (2 papers) and Amoebic Infections and Treatments (2 papers). The work is most often cited by research in Molecular Medicine (164 citations), Endocrinology (48 citations), Infectious Diseases (161 citations), Microbiology (48 citations) and Genetics (113 citations). Nitin Kumar has collaborated with scholars based in United States. Frequent co-authors include Chih‐Chia Su, Edward Yu, Kanagalaghatta R. Rajashankar, Abhijith Radhakrishnan, Jani Reddy Bolla, Jared A. Delmar, Tsung‐Han Chou, Feng Long, Hsiang‐Ting Lei and William M. Shafer. Their work appears in journals such as Protein Science, PLoS ONE, Journal of Biological Chemistry, Nature Communications and Proceedings of the National Academy of Sciences.
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.