J Kassel
Impact in
- Oncology top 0.5%
- Cancer-related Molecular Pathways
- Biotechnology top 0.5%
- Cancer Research and Treatments
Papers in
- Oncology 6
- Cancer-related Molecular Pathways 6
-
- Epigenetics and DNA Methylation 2
- Hedgehog Signaling Pathway Studies 1
- Co-authors
- Stephen Friend (6 shared papers)Joseph F. Fraumeni (1 shared paper)Farideh Z. Bischoff (1 shared paper)Louise C. Strong (1 shared paper)David H. Kim (1 shared paper)Michael A. Tainsky (1 shared paper)David Malkin (1 shared paper)Frederick P. Li (1 shared paper)
- Journals
- Molecular and Cellular Biology (2 papers)Proceedings of the National Academy of Sciences (1 paper)Science (1 paper)PubMed (3 papers)
- Partner nations
- United StatesNorway
In The Last Decade
J Kassel
7 papers receiving 3.7k citations
J Kassel's Hit Papers
Peers
Comparison fields: 5 of 83
- Oncology 2.5k
- Biotechnology 650
- Cancer Research 866
- Molecular Biology 2.1k
- Pathology and Forensic Medicine 451
Countries citing papers authored by J Kassel
This map shows the geographic impact of J Kassel'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 J Kassel with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites J Kassel more than expected).
Fields of papers citing papers by J Kassel
This network shows the impact of papers produced by J Kassel. 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 J Kassel. The network helps show where J Kassel may publish in the future.
Co-authors
The 25 scholars most cited alongside J Kassel, 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 | Germ Line p53 Mutations in a Familial Syndrome of Breast Cancer, Sarcomas, and Other Neoplasms Hit paper breakdown → | 1990 | 2766 |
| 2 | p53 functions as a cell cycle control protein in osteosarcomas. Hit paper breakdown → | 1990 | 674 |
| 3 | 1990 | 208 | |
| 4 | 1992 | 76 | |
| 5 | A functional screen for germ line p53 mutations based on transcriptional activation. | 1992 | 59 |
| 6 | Equal transcription of wild-type and mutant p53 using bicistronic vectors results in the wild-type phenotype. | 1994 | 43 |
| 7 | A functional assay for heterozygous mutations in the GTPase activating protein related domain of the neurofibromatosis type 1 gene. | 1995 | 12 |
About J Kassel
J Kassel is a scholar working on Oncology, Molecular Biology, Genetics, Biotechnology and Neurology, having authored 7 papers that have together received 3.8k indexed citations. Recurring topics across this work include Cancer-related Molecular Pathways (6 papers), Virus-based gene therapy research (3 papers), Cancer Research and Treatments (3 papers), Epigenetics and DNA Methylation (2 papers), Neuroblastoma Research and Treatments (1 paper), Hedgehog Signaling Pathway Studies (1 paper), Neurofibromatosis and Schwannoma Cases (1 paper) and Ocular Oncology and Treatments (1 paper). The work is most often cited by research in Oncology (2.5k citations), Biotechnology (650 citations), Cancer Research (866 citations), Molecular Biology (2.1k citations) and Pathology and Forensic Medicine (451 citations). J Kassel has collaborated with scholars based in United States and Norway. Frequent co-authors include Stephen Friend, Joseph F. Fraumeni, Farideh Z. Bischoff, Louise C. Strong, David H. Kim, Michael A. Tainsky, David Malkin, Frederick P. Li, Lisa Diller and Suzanne J. Baker. Their work appears in journals such as Molecular and Cellular Biology, Proceedings of the National Academy of Sciences, Science and PubMed.
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.