Sudhir Kumar
Impact in
- Plant Science top 0.01%
- Plant-Microbe Interactions and Immunity
- Plant Virus Research Studies
- Plant Molecular Biology Research
- Ecology top 0.01%
- Microbial Community Ecology and Physiology
Papers in
- Genetics 109
- Genetic diversity and population structure 61
- Evolution and Genetic Dynamics 37
- Paleontology 27
- Evolution and Paleontology Studies 24
- Co-authors
- Koichiro TamuraGlen StecherM NeiAlan FilipskiDaniel S. PetersonJoel T. DudleyMasatoshi NeiDaniel G. Peterson
- Journals
- Molecular Biology and Evolution (64 papers)Bioinformatics (22 papers)Genetics (8 papers)Proceedings of the National Academy of Sciences (6 papers)BMC Bioinformatics (6 papers)
- Partner nations
- United StatesSaudi ArabiaIndia
In The Last Decade
Sudhir Kumar
276 papers receiving 218.9k citations
Hit Papers
Peers
Comparison fields: 5 of 221
- Plant Science 64.6k
- Ecology 43.5k
- Parasitology 10.7k
- Endocrinology 8.1k
- Horticulture 1.5k
Countries citing papers authored by Sudhir Kumar
This map shows the geographic impact of Sudhir 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 Sudhir Kumar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sudhir Kumar more than expected).
Fields of papers citing papers by Sudhir Kumar
This network shows the impact of papers produced by Sudhir 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 Sudhir Kumar. The network helps show where Sudhir Kumar may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Sudhir 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 | 2025 | 0 | |
| 2 | 2024 | 0 | |
| 3 | 2024 | 1 | |
| 4 | 2024 | 5 | |
| 5 | 2023 | 1 | |
| 6 | 2023 | 0 | |
| 7 | TimeTree 5: An Expanded Resource for Species Divergence Times Hit paper breakdown → | 2022 | 656 |
| 8 | 2021 | 14 | |
| 9 | 2021 | 8 | |
| 10 | 2020 | 8 | |
| 11 | 2020 | 122 | |
| 12 | 2020 | 10 | |
| 13 | 2020 | 12 | |
| 14 | 2019 | 23 | |
| 15 | 2019 | 38 | |
| 16 | 2019 | 51 | |
| 17 | 2018 | 20 | |
| 18 | 2018 | 23 | |
| 19 | Application of substance-field analysis for failure analysis | 2013 | 3 |
| 20 | 2005 | 116 |
About Sudhir Kumar
Sudhir Kumar is a scholar working on Genetics, Paleontology, Molecular Biology, Cancer Research and Biophysics, having authored 302 papers that have together received 224.1k indexed citations. Recurring topics across this work include Genomics and Phylogenetic Studies (124 papers), Genetic diversity and population structure (61 papers), Evolution and Genetic Dynamics (37 papers), RNA and protein synthesis mechanisms (26 papers), Evolution and Paleontology Studies (24 papers), Cancer Genomics and Diagnostics (19 papers), Gene expression and cancer classification (17 papers) and Chromosomal and Genetic Variations (16 papers). The work is most often cited by research in Plant Science (64.6k citations), Ecology (43.5k citations), Parasitology (10.7k citations), Endocrinology (8.1k citations) and Horticulture (1.5k citations). Sudhir Kumar has collaborated with scholars based in United States, Saudi Arabia and India. Frequent co-authors include Koichiro Tamura, Glen Stecher, M Nei, Alan Filipski, Daniel S. Peterson, Joel T. Dudley, Masatoshi Nei, Daniel G. Peterson, Michael Li and S. Blair Hedges. Their work appears in journals such as Molecular Biology and Evolution, Bioinformatics, Genetics, Proceedings of the National Academy of Sciences and BMC Bioinformatics.
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.