Peter M. Howley
Impact in
- Oncology top 0.02%
- Cancer-related Molecular Pathways
- Epidemiology top 0.01%
- Cervical Cancer and HPV Research
- Hepatitis B Virus Studies
Papers in
- Co-authors
- Martin Scheffner (19 shared papers)Karl Münger (30 shared papers)Jon M. Huibregtse (19 shared papers)Bruce A. Werness (4 shared papers)Arnold J. Levine (2 shared papers)William C. Phelps (12 shared papers)Nicholas J. Dyson (2 shared papers)Ed Harlow (1 shared paper)
- Journals
- Journal of Virology (70 papers)Proceedings of the National Academy of Sciences (30 papers)Molecular and Cellular Biology (26 papers)Virology (14 papers)Journal of Biological Chemistry (10 papers)
- Partner nations
- United StatesGermanyJapan
In The Last Decade
Peter M. Howley
243 papers receiving 39.0k citations
Peter M. Howley's Hit Papers
Peers
Comparison fields: 5 of 145
- Oncology 15.0k
- Epidemiology 17.1k
- Genetics 10.2k
- Virology 1.7k
- Immunology 6.7k
Countries citing papers authored by Peter M. Howley
This map shows the geographic impact of Peter M. Howley'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 Peter M. Howley with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Peter M. Howley more than expected).
Fields of papers citing papers by Peter M. Howley
This network shows the impact of papers produced by Peter M. Howley. 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 Peter M. Howley. The network helps show where Peter M. Howley may publish in the future.
Co-authors
The 25 scholars most cited alongside Peter M. Howley, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 244 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | The E6 oncoprotein encoded by human papillomavirus types 16 and 18 promotes the degradation of p53 Hit paper breakdown → | 1990 | 3311 |
| 2 | The Human Papilloma Virus-16 E7 Oncoprotein Is Able to Bind to the Retinoblastoma Gene Product Hit paper breakdown → | 1989 | 2483 |
| 3 | Association of Human Papillomavirus Types 16 and 18 E6 Proteins with p53 Hit paper breakdown → | 1990 | 2130 |
| 4 | The HPV-16 E6 and E6-AP complex functions as a ubiquitin-protein ligase in the ubiquitination of p53 Hit paper breakdown → | 1993 | 1957 |
| 5 | The E6 and E7 genes of the human papillomavirus type 16 together are necessary and sufficient for transformation of primary human keratinocytes Hit paper breakdown → | 1989 | 1125 |
| 6 | Complex formation of human papillomavirus E7 proteins with the retinoblastoma tumor suppressor gene product. Hit paper breakdown → | 1989 | 971 |
| 7 | The state of the p53 and retinoblastoma genes in human cervical carcinoma cell lines. Hit paper breakdown → | 1991 | 736 |
| 8 | A cellular protein mediates association of p53 with the E6 oncoprotein of human papillomavirus types 16 or 18. Hit paper breakdown → | 1991 | 699 |
| 9 | Structural and transcriptional analysis of human papillomavirus type 16 sequences in cervical carcinoma cell lines Hit paper breakdown → | 1987 | 661 |
| 10 | Virus Infection Induces the Assembly of Coordinately Activated Transcription Factors on the IFN-β Enhancer In Vivo Hit paper breakdown → | 1998 | 642 |
| 11 | Human papillomavirus immortalization and transformation functions Hit paper breakdown → | 2002 | 586 |
| 12 | The human papillomavirus type 16 E7 gene encodes transactivation and transformation functions similar to those of adenovirus E1A Hit paper breakdown → | 1988 | 580 |
| 13 | In vivo ubiquitination and proteasome-mediated degradation of p53(1). Hit paper breakdown → | 1996 | 573 |
| 14 | TGF-β1 inhibition of c-myc transcription and growth in keratinocytes is abrogated by viral transforming proteins with pRB binding domains Hit paper breakdown → | 1990 | 545 |
| 15 | Presence and expression of human papillomavirus sequences in human cervical carcinoma cell lines. Hit paper breakdown → | 1985 | 532 |
| 16 | Adenovirus E1A, simian virus 40 tumor antigen, and human papillomavirus E7 protein share the capacity to disrupt the interaction between transcription factor E2F and the retinoblastoma gene product. Hit paper breakdown → | 1992 | 502 |
| 17 | 1998 | 492 | |
| 18 | 1999 | 450 | |
| 19 | 1993 | 450 | |
| 20 | 2011 | 412 |
About Peter M. Howley
Peter M. Howley is a scholar working on Genetics, Oncology, Epidemiology, Molecular Biology and Immunology, having authored 244 papers that have together received 40.4k indexed citations. Recurring topics across this work include Virus-based gene therapy research (102 papers), Cervical Cancer and HPV Research (84 papers), Cancer-related Molecular Pathways (55 papers), Polyomavirus and related diseases (34 papers), T-cell and Retrovirus Studies (32 papers), Ubiquitin and proteasome pathways (30 papers), Molecular Biology Techniques and Applications (26 papers) and Animal Disease Management and Epidemiology (22 papers). The work is most often cited by research in Oncology (15.0k citations), Epidemiology (17.1k citations), Genetics (10.2k citations), Virology (1.7k citations) and Immunology (6.7k citations). Peter M. Howley has collaborated with scholars based in United States, Germany and Japan. Frequent co-authors include Martin Scheffner, Karl Münger, Jon M. Huibregtse, Bruce A. Werness, Arnold J. Levine, William C. Phelps, Nicholas J. Dyson, Ed Harlow, Carole Yee and Richard D. Vierstra. Their work appears in journals such as Journal of Virology, Proceedings of the National Academy of Sciences, Molecular and Cellular Biology, Virology and Journal of Biological Chemistry.
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.