Namit Kumar
Impact in
- Aging top 2%
- Genetics, Aging, and Longevity in Model Organisms
- Biophysics top 5%
- Cell Image Analysis Techniques
Papers in
-
- Single-cell and spatial transcriptomics 3
- Advanced biosensing and bioanalysis techniques 2
- Renal and related cancers 2
- Genetics 5
- Digestive system and related health 4
- Co-authors
- Svetlana Sadekova (1 shared paper)Lixia Li (1 shared paper)Terrill K. McClanahan (1 shared paper)Renée Moore (1 shared paper)Vanessa M. Peterson (1 shared paper)Douglas C. Wilson (1 shared paper)Joel A. Klappenbach (1 shared paper)Jerelyn Wong (1 shared paper)
- Journals
- Behavioral Neuroscience (2 papers)Development (2 papers)Scientific Reports (1 paper)Materials Today (1 paper)Nature Reviews Drug Discovery (1 paper)
- Partner nations
- United StatesUnited KingdomIndia
In The Last Decade
Namit Kumar
15 papers receiving 1.2k citations
Hit Papers
Peers
Comparison fields: 5 of 109
- Aging 103
- Biophysics 110
- Cancer Research 196
- Molecular Biology 858
- Endocrine and Autonomic Systems 76
Countries citing papers authored by Namit Kumar
This map shows the geographic impact of Namit 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 Namit Kumar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Namit Kumar more than expected).
Fields of papers citing papers by Namit Kumar
This network shows the impact of papers produced by Namit 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 Namit Kumar. The network helps show where Namit Kumar may publish in the future.
Co-authors
The 25 scholars most cited alongside Namit 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 | Multiplexed quantification of proteins and transcripts in single cells Hit paper breakdown → | 2017 | 600 |
| 2 | Applications of single-cell RNA sequencing in drug discovery and development Hit paper breakdown → | 2023 | 205 |
| 3 | 1997 | 66 | |
| 4 | 2018 | 57 | |
| 5 | 1997 | 56 | |
| 6 | 2019 | 45 | |
| 7 | 2011 | 37 | |
| 8 | 2023 | 36 | |
| 9 | 2010 | 35 | |
| 10 | 2014 | 35 | |
| 11 | 2018 | 26 | |
| 12 | 2016 | 18 | |
| 13 | 2016 | 18 | |
| 14 | 2022 | 5 | |
| 15 | 2021 | 2 | |
| 16 | 2024 | 0 | |
| 17 | 2025 | 0 |
About Namit Kumar
Namit Kumar is a scholar working on Molecular Biology, Genetics, Cancer Research, Oncology and Surgery, having authored 17 papers that have together received 1.2k indexed citations. Recurring topics across this work include Digestive system and related health (4 papers), Single-cell and spatial transcriptomics (3 papers), Cancer Genomics and Diagnostics (3 papers), Advanced biosensing and bioanalysis techniques (2 papers), Cell Image Analysis Techniques (2 papers), Genetic factors in colorectal cancer (2 papers), Renal and related cancers (2 papers) and Cancer Cells and Metastasis (2 papers). The work is most often cited by research in Aging (103 citations), Biophysics (110 citations), Cancer Research (196 citations), Molecular Biology (858 citations) and Endocrine and Autonomic Systems (76 citations). Namit Kumar has collaborated with scholars based in United States, United Kingdom and India. Frequent co-authors include Svetlana Sadekova, Lixia Li, Terrill K. McClanahan, Renée Moore, Vanessa M. Peterson, Douglas C. Wilson, Joel A. Klappenbach, Jerelyn Wong, Gloria Rambaldini and Glenn E. Morrison. Their work appears in journals such as Behavioral Neuroscience, Development, Scientific Reports, Materials Today and Nature Reviews Drug Discovery.
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.