David Gennert
Impact in
- Immunology top 1%
- Immune Cell Function and Interaction
- Immune cells in cancer
- T-cell and B-cell Immunology
- Cancer Research top 2%
Papers in
-
- Single-cell and spatial transcriptomics 4
- RNA Research and Splicing 4
- RNA modifications and cancer 2
- CRISPR and Genetic Engineering 2
- Oncology 3
- CAR-T cell therapy research 3
- Co-authors
- Aviv Regev (5 shared papers)Rahul Satija (3 shared papers)Jeffrey A. Farrell (1 shared paper)Alexander F. Schier (1 shared paper)Alex K. Shalek (3 shared papers)John J. Trombetta (3 shared papers)Ansuman T. Satpathy (5 shared papers)Howard Y. Chang (4 shared papers)
- Journals
- Nature Communications (2 papers)Nature (2 papers)Nature Methods (1 paper)Expert Opinion on Therapeutic Patents (1 paper)Cell (1 paper)
- Partner nations
- United StatesChinaHong Kong
In The Last Decade
David Gennert
14 papers receiving 5.3k citations
David Gennert's Hit Papers
Peers
Comparison fields: 5 of 127
- Immunology 1.4k
- Cancer Research 678
- Biophysics 278
- Molecular Biology 3.2k
- Oncology 1.1k
Countries citing papers authored by David Gennert
This map shows the geographic impact of David Gennert'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 David Gennert with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David Gennert more than expected).
Fields of papers citing papers by David Gennert
This network shows the impact of papers produced by David Gennert. 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 David Gennert. The network helps show where David Gennert may publish in the future.
Co-authors
The 25 scholars most cited alongside David Gennert, 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 | Spatial reconstruction of single-cell gene expression data Hit paper breakdown → | 2015 | 3890 |
| 2 | c-Jun overexpression in CAR T cells induces exhaustion resistance Hit paper breakdown → | 2019 | 548 |
| 3 | 2016 | 278 | |
| 4 | 2014 | 264 | |
| 5 | 2014 | 177 | |
| 6 | 2019 | 66 | |
| 7 | 2021 | 45 | |
| 8 | 2025 | 13 | |
| 9 | 2025 | 5 | |
| 10 | 2026 | 1 | |
| 11 | Single-cell transcriptomics reveals bimodality in expression and splicing in immune cells | 2013 | 1 |
| 12 | 2019 | 1 | |
| 13 | 2018 | 1 | |
| 14 | 2025 | 1 | |
| 15 | 2026 | 0 | |
| 16 | 2025 | 0 |
About David Gennert
David Gennert is a scholar working on Molecular Biology, Oncology, Immunology, Cancer Research and Infectious Diseases, having authored 16 papers that have together received 5.3k indexed citations. Recurring topics across this work include Single-cell and spatial transcriptomics (4 papers), RNA Research and Splicing (4 papers), CAR-T cell therapy research (3 papers), T-cell and B-cell Immunology (2 papers), Immune Cell Function and Interaction (2 papers), RNA modifications and cancer (2 papers), CRISPR and Genetic Engineering (2 papers) and Cancer-related molecular mechanisms research (2 papers). The work is most often cited by research in Immunology (1.4k citations), Cancer Research (678 citations), Biophysics (278 citations), Molecular Biology (3.2k citations) and Oncology (1.1k citations). David Gennert has collaborated with scholars based in United States, China and Hong Kong. Frequent co-authors include Aviv Regev, Rahul Satija, Jeffrey A. Farrell, Alexander F. Schier, Alex K. Shalek, John J. Trombetta, Ansuman T. Satpathy, Howard Y. Chang, Jeffrey M. Granja and Elena Sotillo. Their work appears in journals such as Nature Communications, Nature, Nature Methods, Expert Opinion on Therapeutic Patents and Cell.
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.