Gianluca Canettieri
- Molecular Biology top 2%
- Surgery top 5%
- Oncology top 5%
- Endocrinology, Diabetes and Metabolism top 2%
- Genetics top 5%
- Co-authors
- Marc MontminyRobert A. ScreatonMichael D. ConkrightErnesto GuzmánJohn B. HogeneschLucia Di MarcotullioJennifer L. BestSonia Coni
- Topics
- Epigenetics and DNA Methylation (31 papers)Hedgehog Signaling Pathway Studies (27 papers)Genomics and Chromatin Dynamics (10 papers)
- Partner nations
- ItalyUnited StatesGermany
In The Last Decade
Gianluca Canettieri
75 papers receiving 4.8k citations
Hit Papers
Peers
Comparison fields: 5 of 122
- Molecular Biology 3.4k
- Surgery 808
- Oncology 668
- Endocrinology, Diabetes and Metabolism 656
- Genetics 636
Countries citing papers authored by Gianluca Canettieri
This map shows the geographic impact of Gianluca Canettieri'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 Gianluca Canettieri with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gianluca Canettieri more than expected).
Fields of papers citing papers by Gianluca Canettieri
This network shows the impact of papers produced by Gianluca Canettieri. 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 Gianluca Canettieri. The network helps show where Gianluca Canettieri may publish in the future.
Co-authorship network of co-authors of Gianluca Canettieri
This figure shows the co-authorship network connecting the top 25 collaborators of Gianluca Canettieri. A scholar is included among the top collaborators of Gianluca Canettieri 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 Gianluca Canettieri. Gianluca Canettieri is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 3 | |
| 3 | 3 | |
| 4 | 1 | |
| 5 | 4 | |
| 6 | 19 | |
| 7 | 0 | |
| 8 | 12 | |
| 9 | 44 | |
| 10 | 39 | |
| 11 | 3 | |
| 12 | 95 | |
| 13 | 41 | |
| 14 | 19 | |
| 15 | 17 | |
| 16 | The CREB Coactivator TORC2 Functions as a Calcium- and cAMP-Sensitive Coincidence Detectorbreakdown → | 541 |
| 17 | 466 | |
| 18 | 160 | |
| 19 | 1 | |
| 20 | 52 |
About Gianluca Canettieri
Gianluca Canettieri is a scholar working on Molecular Biology, Biochemistry and Oncology, having authored 76 papers that have together received 4.9k indexed citations. Recurring topics across this work include Epigenetics and DNA Methylation (31 papers), Hedgehog Signaling Pathway Studies (27 papers) and Genomics and Chromatin Dynamics (10 papers). The work is most often cited by research in Molecular Biology (3.4k citations), Endocrinology, Diabetes and Metabolism (656 citations) and Aging (68 citations). Gianluca Canettieri has collaborated with scholars based in Italy, United States and Germany. Frequent co-authors include Marc Montminy, Robert A. Screaton, Michael D. Conkright, Ernesto Guzmán, John B. Hogenesch, Lucia Di Marcotullio, Jennifer L. Best, Sonia Coni, Alberto Gulino and Isabella Screpanti. Their work appears in journals such as New England Journal of Medicine, Cell and Proceedings of the National Academy of Sciences.
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.