Massimo Cancemi
Impact in
- Genetics top 10%
- Estrogen and related hormone effects
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- Breast Cancer Treatment Studies
- Cancer, Lipids, and Metabolism
Papers in
- Genetics 7
- Estrogen and related hormone effects 7
- Mesenchymal stem cell research 1
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- Cancer, Lipids, and Metabolism 2
- Co-authors
- Lucia Altucci (10 shared papers)Luigi Cicatiello (9 shared papers)Alessandro Weisz (9 shared papers)Francesco Bresciani (9 shared papers)Raffaele Addeo (5 shared papers)Valeria Belsito Petrizzi (5 shared papers)Claudio Scafoglio (2 shared papers)Silvana Caristi (3 shared papers)
- Journals
- Molecular Biology of the Cell (1 paper)Journal of Molecular Endocrinology (1 paper)Stem Cells and Development (1 paper)Biochemical and Biophysical Research Communications (1 paper)Breast Cancer Research and Treatment (1 paper)
- Partner nations
- ItalyNetherlandsJapan
In The Last Decade
Massimo Cancemi
10 papers receiving 417 citations
Peers
Comparison fields: 5 of 48
- Genetics 210
- Cancer Research 84
- Oncology 44
- Geriatrics and Gerontology 5
- Molecular Biology 84
Countries citing papers authored by Massimo Cancemi
This map shows the geographic impact of Massimo Cancemi'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 Massimo Cancemi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Massimo Cancemi more than expected).
Fields of papers citing papers by Massimo Cancemi
This network shows the impact of papers produced by Massimo Cancemi. 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 Massimo Cancemi. The network helps show where Massimo Cancemi may publish in the future.
Co-authors
The 25 scholars most cited alongside Massimo Cancemi, 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 | 2004 | 145 | |
| 2 | 1997 | 79 | |
| 3 | 2004 | 77 | |
| 4 | Estrogens do not modify MAP kinase-dependent nuclear signaling during stimulation of early G(1) progression in human breast cancer cells. | 2001 | 33 |
| 5 | 1996 | 32 | |
| 6 | Constitutive overexpression of cyclin D1 does not prevent inhibition of hormone-responsive human breast cancer cell growth by antiestrogens. | 1998 | 32 |
| 7 | 2013 | 18 | |
| 8 | 2003 | 15 | |
| 9 | 2001 | 3 | |
| 10 | 2001 | 2 |
About Massimo Cancemi
Massimo Cancemi is a scholar working on Genetics, Cancer Research, Genetics, Molecular Biology and Nuclear Energy and Engineering, having authored 10 papers that have together received 436 indexed citations. Recurring topics across this work include Estrogen and related hormone effects (7 papers), Cancer, Lipids, and Metabolism (2 papers), Pluripotent Stem Cells Research (1 paper) and Mesenchymal stem cell research (1 paper). The work is most often cited by research in Genetics (210 citations), Cancer Research (84 citations), Oncology (44 citations), Geriatrics and Gerontology (5 citations) and Molecular Biology (84 citations). Massimo Cancemi has collaborated with scholars based in Italy, Netherlands and Japan. Frequent co-authors include Lucia Altucci, Luigi Cicatiello, Alessandro Weisz, Francesco Bresciani, Raffaele Addeo, Valeria Belsito Petrizzi, Claudio Scafoglio, Silvana Caristi, Simona Caporali and Carmen Pacilio. Their work appears in journals such as Molecular Biology of the Cell, Journal of Molecular Endocrinology, Stem Cells and Development, Biochemical and Biophysical Research Communications and Breast Cancer Research and Treatment.
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.