Christopher C. Govern
Impact in
- Immunology top 10%
- T-cell and B-cell Immunology
- Immune Cell Function and Interaction
- Immunotherapy and Immune Responses
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- Advanced Thermodynamics and Statistical Mechanics
Papers in
-
- Gene Regulatory Network Analysis 7
- Single-cell and spatial transcriptomics 2
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- T-cell and B-cell Immunology 4
- Immune Cell Function and Interaction 3
- Co-authors
- Pieter Rein ten Wolde (3 shared papers)Arup K. Chakraborty (9 shared papers)Ming Yang (5 shared papers)Jeroen P. Roose (5 shared papers)Mary Ho (3 shared papers)Jayajit Das (3 shared papers)Arthur Weiss (3 shared papers)Julie Zikherman (3 shared papers)
- Journals
- Proceedings of the National Academy of Sciences (3 papers)PLoS ONE (2 papers)Physical Review Letters (2 papers)Science Signaling (2 papers)Cell (1 paper)
- Partner nations
- United StatesNetherlands
In The Last Decade
Christopher C. Govern
13 papers receiving 732 citations
Peers
Comparison fields: 5 of 80
- Immunology 304
- Statistical and Nonlinear Physics 109
- Biophysics 36
- Oncology 139
- Molecular Biology 360
Countries citing papers authored by Christopher C. Govern
This map shows the geographic impact of Christopher C. Govern'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 Christopher C. Govern with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Christopher C. Govern more than expected).
Fields of papers citing papers by Christopher C. Govern
This network shows the impact of papers produced by Christopher C. Govern. 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 Christopher C. Govern. The network helps show where Christopher C. Govern may publish in the future.
Co-authors
The 23 scholars most cited alongside Christopher C. Govern, 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 | 2009 | 314 | |
| 2 | 2010 | 118 | |
| 3 | 2014 | 96 | |
| 4 | 2014 | 72 | |
| 5 | Dysregulated RasGRP1 Responds to Cytokine Receptor Input in T Cell Leukemogenesis | 2012 | 40 |
| 6 | 2012 | 34 | |
| 7 | 2012 | 25 | |
| 8 | 2009 | 20 | |
| 9 | Molecular Origin and Functional Consequences of Digital Signaling and Hysteresis During Ras Activation in Lymphocytes | 2009 | 8 |
| 10 | 2009 | 3 | |
| 11 | Identifying Dynamical Bottlenecks of Stochastic Transitions in Biochemical Networks | 2011 | 2 |
| 12 | 2013 | 1 | |
| 13 | 2013 | 1 |
About Christopher C. Govern
Christopher C. Govern is a scholar working on Molecular Biology, Immunology, Statistical and Nonlinear Physics, Public Health, Environmental and Occupational Health and Physical and Theoretical Chemistry, having authored 13 papers that have together received 734 indexed citations. Recurring topics across this work include Gene Regulatory Network Analysis (7 papers), T-cell and B-cell Immunology (4 papers), Immune Cell Function and Interaction (3 papers), Advanced Thermodynamics and Statistical Mechanics (2 papers), Chronic Myeloid Leukemia Treatments (2 papers), Acute Lymphoblastic Leukemia research (2 papers), Single-cell and spatial transcriptomics (2 papers) and Molecular Communication and Nanonetworks (2 papers). The work is most often cited by research in Immunology (304 citations), Statistical and Nonlinear Physics (109 citations), Biophysics (36 citations), Oncology (139 citations) and Molecular Biology (360 citations). Christopher C. Govern has collaborated with scholars based in United States and Netherlands. Frequent co-authors include Pieter Rein ten Wolde, Arup K. Chakraborty, Ming Yang, Jeroen P. Roose, Mary Ho, Jayajit Das, Arthur Weiss, Julie Zikherman, Eric S. Huseby and Michelle K. Paczosa. Their work appears in journals such as Proceedings of the National Academy of Sciences, PLoS ONE, Physical Review Letters, Science Signaling 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.