Brad Efron
Impact in
- Infectious Diseases top 1%
- Tuberculosis Research and Epidemiology
- HIV/AIDS drug development and treatment
- HIV/AIDS Research and Interventions
- Virology top 5%
- HIV Research and Treatment
Papers in
-
- Gene expression and cancer classification 2
- RNA and protein synthesis mechanisms 1
-
- HIV/AIDS Research and Interventions 1
- Tuberculosis Research and Epidemiology 1
- Co-authors
- Martin I. Voskuil (1 shared paper)Sabine Ehrt (1 shared paper)Dirk Schnappinger (1 shared paper)Joseph A. Mangan (1 shared paper)Gary K. Schoolnik (1 shared paper)Carl Nathan (1 shared paper)Gregory Dolganov (1 shared paper)Yang Liu (1 shared paper)
- Journals
- The Journal of Experimental Medicine (1 paper)Statistical Applications in Genetics and Molecular Biology (1 paper)Annals of Internal Medicine (1 paper)Journal of the American Statistical Association (1 paper)Journal of Pediatric Surgery (1 paper)
- Partner nations
- United StatesUnited Kingdom
In The Last Decade
Brad Efron
6 papers receiving 1.5k citations
Brad Efron's Hit Papers
Peers
Comparison fields: 5 of 97
- Infectious Diseases 1.1k
- Virology 170
- Molecular Medicine 173
- Epidemiology 720
- Molecular Biology 588
Countries citing papers authored by Brad Efron
This map shows the geographic impact of Brad Efron'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 Brad Efron with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Brad Efron more than expected).
Fields of papers citing papers by Brad Efron
This network shows the impact of papers produced by Brad Efron. 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 Brad Efron. The network helps show where Brad Efron may publish in the future.
Co-authors
The 23 scholars most cited alongside Brad Efron, 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 | Transcriptional Adaptation of Mycobacterium tuberculosis within Macrophages Hit paper breakdown → | 2003 | 1114 |
| 2 | 1999 | 176 | |
| 3 | 2002 | 96 | |
| 4 | 2001 | 74 | |
| 5 | 2004 | 51 | |
| 6 | 1991 | 40 |
About Brad Efron
Brad Efron is a scholar working on Molecular Biology, Infectious Diseases, Statistics and Probability, Surgery and Virology, having authored 6 papers that have together received 1.6k indexed citations. Recurring topics across this work include Gene expression and cancer classification (2 papers), Statistical Methods in Clinical Trials (2 papers), Intestinal Malrotation and Obstruction Disorders (1 paper), HIV Research and Treatment (1 paper), Health Systems, Economic Evaluations, Quality of Life (1 paper), RNA and protein synthesis mechanisms (1 paper), HIV/AIDS Research and Interventions (1 paper) and Tuberculosis Research and Epidemiology (1 paper). The work is most often cited by research in Infectious Diseases (1.1k citations), Virology (170 citations), Molecular Medicine (173 citations), Epidemiology (720 citations) and Molecular Biology (588 citations). Brad Efron has collaborated with scholars based in United States and United Kingdom. Frequent co-authors include Martin I. Voskuil, Sabine Ehrt, Dirk Schnappinger, Joseph A. Mangan, Gary K. Schoolnik, Carl Nathan, Gregory Dolganov, Yang Liu, Irene M. Monahan and Philip D. Butcher. Their work appears in journals such as The Journal of Experimental Medicine, Statistical Applications in Genetics and Molecular Biology, Annals of Internal Medicine, Journal of the American Statistical Association and Journal of Pediatric Surgery.
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.