J Kassel
- Oncology top 1%
- Cancer-related Molecular Pathways 6
- Biotechnology top 0.5%
- Cancer Research and Treatments 3
- Cancer Research top 2%
- Molecular Biology top 5%
- Epigenetics and DNA Methylation 2
- RNA modifications and cancer 1
- Hedgehog Signaling Pathway Studies 1
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- Virus-based gene therapy research 3
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- Neuroblastoma Research and Treatments 1
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- Microtubule and mitosis dynamics 1
- Co-authors
- Stephen FriendJoseph F. FraumeniDavid MalkinFrederick P. LiFarideh Z. BischoffDavid H. KimMichael A. TainskyLouise C. Strong
- Cited by
- OncologyBiotechnologyCancer Research
- Journals
- Molecular and Cellular Biology (2 papers)Science (1 paper)Proceedings of the National Academy of Sciences (1 paper)
- Partner nations
- United StatesNorway
In The Last Decade
J Kassel
7 papers receiving 3.7k citations
Hit Papers
Peers
Comparison fields: 5 of 84
- Oncology 2.6k
- Biotechnology 673
- Cancer Research 955
- Molecular Biology 2.2k
- Pathology and Forensic Medicine 502
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-authorship network
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 | A functional assay for heterozygous mutations in the GTPase activating protein related domain of the neurofibromatosis type 1 gene. | 1995 | 12 |
| 2 | Equal transcription of wild-type and mutant p53 using bicistronic vectors results in the wild-type phenotype. | 1994 | 43 |
| 3 | 1992 | 76 | |
| 4 | A functional screen for germ line p53 mutations based on transcriptional activation. | 1992 | 59 |
| 5 | 1990 | 209 | |
| 6 | Germ Line p53 Mutations in a Familial Syndrome of Breast Cancer, Sarcomas, and Other Neoplasmsbreakdown → | 1990 | 2766 |
| 7 | p53 functions as a cell cycle control protein in osteosarcomas.breakdown → | 1990 | 677 |
About J Kassel
J Kassel is a scholar working on Biotechnology, Oncology, Ophthalmology, Genetics 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), RNA modifications and cancer (1 paper), Microtubule and mitosis dynamics (1 paper) and Hedgehog Signaling Pathway Studies (1 paper). The work is most often cited by research in Oncology (2.6k citations), Biotechnology (673 citations), Cancer Research (955 citations), Molecular Biology (2.2k citations) and Pathology and Forensic Medicine (502 citations). J Kassel has collaborated with scholars based in United States and Norway. Frequent co-authors include Stephen Friend, Joseph F. Fraumeni, David Malkin, Frederick P. Li, Farideh Z. Bischoff, David H. Kim, Michael A. Tainsky, Louise C. Strong, Mehmet Öztürk and Bert Vogelstein. Their work appears in journals such as Molecular and Cellular Biology, Science, Proceedings of the National Academy of Sciences 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.