Jeffery S. Cox
- Infectious Diseases top 0.1%
- Tuberculosis Research and Epidemiology 40
- Molecular Medicine top 0.2%
- Antibiotic Resistance in Bacteria 12
- Epidemiology top 0.2%
- Mycobacterium research and diagnosis 22
- Autophagy in Disease and Therapy 9
- Cell Biology top 0.2%
- Endocrinology top 0.5%
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- interferon and immune responses 8
- Immune Response and Inflammation 8
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- RNA and protein synthesis mechanisms 7
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- Bacterial Genetics and Biotechnology 6
- Co-authors
- Peter WalterPaolo ManzanilloCaroline E. ShamuWilliam R. JacobsSarah A. StanleyRobert O. WatsonSridharan RaghavanMichael U. Shiloh
- Partner nations
- United StatesSouth AfricaNetherlands
In The Last Decade
Jeffery S. Cox
74 papers receiving 13.1k citations
Hit Papers
Peers
Comparison fields: 5 of 136
- Infectious Diseases 5.7k
- Molecular Medicine 1.4k
- Epidemiology 5.6k
- Cell Biology 2.3k
- Endocrinology 687
Countries citing papers authored by Jeffery S. Cox
This map shows the geographic impact of Jeffery S. Cox'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 Jeffery S. Cox with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jeffery S. Cox more than expected).
Fields of papers citing papers by Jeffery S. Cox
This network shows the impact of papers produced by Jeffery S. Cox. 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 Jeffery S. Cox. The network helps show where Jeffery S. Cox may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Jeffery S. Cox, 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 | 2023 | 49 | |
| 3 | 2023 | 11 | |
| 4 | 2022 | 26 | |
| 5 | 2021 | 58 | |
| 6 | 2017 | 28 | |
| 7 | 2017 | 34 | |
| 8 | The Cytosolic Sensor cGAS Detects Mycobacterium tuberculosis DNA to Induce Type I Interferons and Activate Autophagybreakdown → | 2015 | 469 |
| 9 | 2014 | 17 | |
| 10 | Circadian Gene Bmal1 Regulates Diurnal Oscillations of Ly6C hi Inflammatory Monocytesbreakdown → | 2013 | 505 |
| 11 | 2013 | 82 | |
| 12 | 2012 | 347 | |
| 13 | 2009 | 392 | |
| 14 | 2009 | 258 | |
| 15 | 2007 | 324 | |
| 16 | Type VII secretion — mycobacteria show the waybreakdown → | 2007 | 556 |
| 17 | 2007 | 39 | |
| 18 | 2006 | 167 | |
| 19 | 2005 | 150 | |
| 20 | 1997 | 327 |
About Jeffery S. Cox
Jeffery S. Cox is a scholar working on Molecular Medicine, Infectious Diseases and Immunology, having authored 75 papers that have together received 13.2k indexed citations. Recurring topics across this work include Tuberculosis Research and Epidemiology (40 papers), Mycobacterium research and diagnosis (22 papers), Antibiotic Resistance in Bacteria (12 papers), Autophagy in Disease and Therapy (9 papers), interferon and immune responses (8 papers), Immune Response and Inflammation (8 papers), RNA and protein synthesis mechanisms (7 papers) and Bacterial Genetics and Biotechnology (6 papers). The work is most often cited by research in Infectious Diseases (5.7k citations), Molecular Medicine (1.4k citations) and Epidemiology (5.6k citations). Jeffery S. Cox has collaborated with scholars based in United States, South Africa and Netherlands. Frequent co-authors include Peter Walter, Paolo Manzanillo, Caroline E. Shamu, William R. Jacobs, Sarah A. Stanley, Robert O. Watson, Sridharan Raghavan, Michael U. Shiloh, Rudolf Grosschedl and Klaus Giese. Their work appears in journals such as Nature, Science 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.