Brad Efron
Impact in
- Infectious Diseases top 1%
- Tuberculosis Research and Epidemiology
- HIV/AIDS drug development and treatment
- Molecular Medicine top 2%
- Antibiotic Resistance in Bacteria
Papers in
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- Gene expression and cancer classification 2
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- HIV/AIDS drug development and treatment 1
- Tuberculosis Research and Epidemiology 1
- Co-authors
- Dirk Schnappinger (1 shared paper)Sabine Ehrt (1 shared paper)Gregory Dolganov (1 shared paper)Joseph A. Mangan (1 shared paper)Carl Nathan (1 shared paper)Philip D. Butcher (1 shared paper)Irene M. Monahan (1 shared paper)Martin I. Voskuil (1 shared paper)
- Journals
- Journal of Pediatric Surgery (1 paper)Statistical Applications in Genetics and Molecular Biology (1 paper)Biostatistics (1 paper)Annals of Internal Medicine (1 paper)Journal of the American Statistical Association (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 96
- Infectious Diseases 1.0k
- Molecular Medicine 168
- Virology 114
- Epidemiology 686
- Molecular Biology 540
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 | 1117 |
| 2 | 1999 | 176 | |
| 3 | 2002 | 97 | |
| 4 | 2001 | 75 | |
| 5 | 2004 | 52 | |
| 6 | 1991 | 40 |
About Brad Efron
Brad Efron is a scholar working on Molecular Biology, Infectious Diseases, Statistics and Probability, Epidemiology and Artificial Intelligence, 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), Infant Nutrition and Health (1 paper), HIV/AIDS drug development and treatment (1 paper), Tuberculosis Research and Epidemiology (1 paper), Health Systems, Economic Evaluations, Quality of Life (1 paper), Mycobacterium research and diagnosis (1 paper) and Advanced Causal Inference Techniques (1 paper). The work is most often cited by research in Infectious Diseases (1.0k citations), Molecular Medicine (168 citations), Virology (114 citations), Epidemiology (686 citations) and Molecular Biology (540 citations). Brad Efron has collaborated with scholars based in United States and United Kingdom. Frequent co-authors include Dirk Schnappinger, Sabine Ehrt, Gregory Dolganov, Joseph A. Mangan, Carl Nathan, Philip D. Butcher, Irene M. Monahan, Martin I. Voskuil, Yang Liu and Gary K. Schoolnik. Their work appears in journals such as Journal of Pediatric Surgery, Statistical Applications in Genetics and Molecular Biology, Biostatistics, Annals of Internal Medicine and Journal of the American Statistical Association.
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.