Michael J. Ravitz
Impact in
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- Cancer-related Molecular Pathways
- Pancreatic and Hepatic Oncology Research
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- TGF-β signaling in diseases
- RNA Research and Splicing
- PI3K/AKT/mTOR signaling in cancer
- RNA modifications and cancer
- Ubiquitin and proteasome pathways
Papers in
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- PI3K/AKT/mTOR signaling in cancer 3
- Hedgehog Signaling Pathway Studies 2
- TGF-β signaling in diseases 2
- RNA and protein synthesis mechanisms 1
- Oncology 4
- Cancer-related Molecular Pathways 4
- Co-authors
- Charles E. Wenner (4 shared papers)Mary C. Lynch (3 shared papers)Emmett V. Schmidt (3 shared papers)Li Chen (3 shared papers)Kevin Korenblat (1 shared paper)Michael J. Pazin (1 shared paper)Calogero Dolce (1 shared paper)Alan J. Kinniburgh (1 shared paper)
- Journals
- Journal of Cellular Physiology (2 papers)Molecular and Cellular Biology (1 paper)Cell Cycle (1 paper)Advances in cancer research (1 paper)Cancer Research (1 paper)
- Partner nations
- United States
In The Last Decade
Michael J. Ravitz
7 papers receiving 417 citations
Peers
Comparison fields: 5 of 58
- Oncology 140
- Molecular Biology 307
- Cancer Research 58
- Aging 5
- Immunology 34
Countries citing papers authored by Michael J. Ravitz
This map shows the geographic impact of Michael J. Ravitz'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 Michael J. Ravitz with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael J. Ravitz more than expected).
Fields of papers citing papers by Michael J. Ravitz
This network shows the impact of papers produced by Michael J. Ravitz. 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 Michael J. Ravitz. The network helps show where Michael J. Ravitz may publish in the future.
Co-authors
The 9 scholars most cited alongside Michael J. Ravitz, 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 | 1997 | 132 | |
| 2 | 2005 | 102 | |
| 3 | 2007 | 48 | |
| 4 | Transforming growth factor beta-induced activation of cyclin E-cdk2 kinase and down-regulation of p27Kip1 in C3H 10T1/2 mouse fibroblasts. | 1995 | 43 |
| 5 | 2009 | 41 | |
| 6 | 1996 | 40 | |
| 7 | 1994 | 21 |
About Michael J. Ravitz
Michael J. Ravitz is a scholar working on Molecular Biology, Oncology, Physiology, Biotechnology and Neurology, having authored 7 papers that have together received 427 indexed citations. Recurring topics across this work include Cancer-related Molecular Pathways (4 papers), PI3K/AKT/mTOR signaling in cancer (3 papers), Cancer Research and Treatments (2 papers), Hedgehog Signaling Pathway Studies (2 papers), Tuberous Sclerosis Complex Research (2 papers), TGF-β signaling in diseases (2 papers), Neuroblastoma Research and Treatments (1 paper) and RNA and protein synthesis mechanisms (1 paper). The work is most often cited by research in Oncology (140 citations), Molecular Biology (307 citations), Cancer Research (58 citations), Aging (5 citations) and Immunology (34 citations). Michael J. Ravitz has collaborated with scholars based in United States. Frequent co-authors include Charles E. Wenner, Mary C. Lynch, Emmett V. Schmidt, Li Chen, Kevin Korenblat, Michael J. Pazin, Calogero Dolce, Alan J. Kinniburgh and Tae‐Aug Kim. Their work appears in journals such as Journal of Cellular Physiology, Molecular and Cellular Biology, Cell Cycle, Advances in cancer research and Cancer Research.
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.