Massimo Cancemi

505 total citations
9 papers, 411 citations indexed

About

Massimo Cancemi is a scholar working on Molecular Biology, Genetics and Oncology. According to data from OpenAlex, Massimo Cancemi has authored 9 papers receiving a total of 411 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Molecular Biology, 7 papers in Genetics and 5 papers in Oncology. Recurrent topics in Massimo Cancemi's work include Estrogen and related hormone effects (7 papers), Cancer-related Molecular Pathways (5 papers) and Retinoids in leukemia and cellular processes (3 papers). Massimo Cancemi is often cited by papers focused on Estrogen and related hormone effects (7 papers), Cancer-related Molecular Pathways (5 papers) and Retinoids in leukemia and cellular processes (3 papers). Massimo Cancemi collaborates with scholars based in Italy, Netherlands and United States. Massimo Cancemi's co-authors include Lucia Altucci, Francesco Bresciani, Luigi Cicatiello, Alessandro Weisz, Raffaele Addeo, Valeria Belsito Petrizzi, Claudio Scafoglio, Silvana Caristi, Simona Caporali and Carmen Pacilio and has published in prestigious journals such as Molecular and Cellular Biology, Biochemical and Biophysical Research Communications and Endocrinology.

In The Last Decade

Massimo Cancemi

9 papers receiving 404 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Massimo Cancemi Italy 8 240 189 165 81 45 9 411
WR Miller United Kingdom 11 195 0.8× 138 0.7× 167 1.0× 80 1.0× 42 0.9× 19 474
Antonietta de Falco Italy 7 277 1.2× 250 1.3× 142 0.9× 55 0.7× 107 2.4× 8 490
Charlotte Andrieu France 8 207 0.9× 116 0.6× 178 1.1× 154 1.9× 38 0.8× 12 441
P. Cannon United Kingdom 7 181 0.8× 183 1.0× 294 1.8× 123 1.5× 53 1.2× 10 496
Y Yamaguchi Japan 6 196 0.8× 142 0.8× 136 0.8× 52 0.6× 53 1.2× 15 384
Sandrine Bonnet France 12 434 1.8× 259 1.4× 162 1.0× 91 1.1× 32 0.7× 16 585
Nobuhiro Ijichi Japan 9 257 1.1× 172 0.9× 80 0.5× 119 1.5× 80 1.8× 18 442
Christina M.W. Chan United Kingdom 9 256 1.1× 259 1.4× 160 1.0× 83 1.0× 44 1.0× 12 463
Elisabetta Marchetti Italy 12 138 0.6× 119 0.6× 114 0.7× 64 0.8× 30 0.7× 37 333
P A O'Neill United Kingdom 7 227 0.9× 197 1.0× 203 1.2× 98 1.2× 25 0.6× 7 425

Countries citing papers authored by Massimo Cancemi

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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-authorship network of co-authors of Massimo Cancemi

This figure shows the co-authorship network connecting the top 25 collaborators of Massimo Cancemi. A scholar is included among the top collaborators of Massimo Cancemi based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Massimo Cancemi. Massimo Cancemi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

9 of 9 papers shown
1.
Miceli, Marco, Gianluigi Franci, Carmela Dell’Aversana, et al.. (2013). MePR: A Novel Human Mesenchymal Progenitor Model with Characteristics of Pluripotency. Stem Cells and Development. 22(17). 2368–2383. 17 indexed citations
2.
3.
Cicatiello, Luigi, Claudio Scafoglio, Lucia Altucci, et al.. (2004). A genomic view of estrogen actions in human breast cancer cells by expression profiling of the hormone-responsive transcriptome. Journal of Molecular Endocrinology. 32(3). 719–775. 75 indexed citations
4.
Caporali, Simona, Manami Imai, Lucia Altucci, et al.. (2003). Distinct Signaling Pathways Mediate Stimulation of Cell Cycle Progression and Prevention of Apoptotic Cell Death by Estrogen in Rat Pituitary Tumor PR1 Cells. Molecular Biology of the Cell. 14(12). 5051–5059. 15 indexed citations
5.
Pacilio, Carmen, Massimo Cancemi, Luigi Cicatiello, et al.. (2001). Inhibition of Human Breast Cancer Cell Growth by Blockade of the Mevalonate-Protein Prenylation Pathway is not Prevented by Overexpression of Cyclin D1. Breast Cancer Research and Treatment. 67(1). 23–33. 3 indexed citations
6.
Caristi, Silvana, Filomena Matarese, Manami Imai, et al.. (2001). Estrogens do not modify MAP kinase-dependent nuclear signaling during stimulation of early G(1) progression in human breast cancer cells.. PubMed. 61(17). 6360–6. 33 indexed citations
7.
Pacilio, Carmen, Raffaele Addeo, Lucia Altucci, et al.. (1998). Constitutive overexpression of cyclin D1 does not prevent inhibition of hormone-responsive human breast cancer cell growth by antiestrogens.. PubMed. 58(5). 871–6. 31 indexed citations
8.
Altucci, Lucia, Raffaele Addeo, Luigi Cicatiello, et al.. (1997). Estrogen Induces Early and Timed Activation of Cyclin-Dependent Kinases 4, 5, and 6 and Increases Cyclin Messenger Ribonucleic Acid Expression in Rat Uterus1. Endocrinology. 138(3). 978–984. 72 indexed citations
9.
Addeo, Raffaele, Lucia Altucci, Teresa Battista, et al.. (1996). Stimulation of Human Breast Cancer MCF-7 Cells with Estrogen Prevents Cell Cycle Arrest by HMG-CoA Reductase Inhibitors. Biochemical and Biophysical Research Communications. 220(3). 864–870. 29 indexed citations

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.

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