Silvio Bicciato
- Molecular Biology top 0.2%
- Cell Biology top 0.05%
- Oncology top 0.5%
- Immunology top 0.5%
- Cancer Research top 0.5%
- Co-authors
- Mattia ForcatoMichelangelo CordenonsiStefano PiccoloFrancesca ZanconatoSirio DupontElena EnzoMariaceleste AragonaStefano Giulitti
- Topics
- Hippo pathway signaling and YAP/TAZ (21 papers)Gene expression and cancer classification (19 papers)Genomics and Chromatin Dynamics (17 papers)
- Journals
- NatureCellNucleic Acids Research
- Partner nations
- ItalyUnited StatesUnited Kingdom
In The Last Decade
Silvio Bicciato
179 papers receiving 18.8k citations
Hit Papers
Peers
Comparison fields: 5 of 180
- Molecular Biology 10.0k
- Cell Biology 7.1k
- Oncology 4.0k
- Immunology 3.4k
- Cancer Research 2.5k
Countries citing papers authored by Silvio Bicciato
This map shows the geographic impact of Silvio Bicciato'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 Silvio Bicciato with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Silvio Bicciato more than expected).
Fields of papers citing papers by Silvio Bicciato
This network shows the impact of papers produced by Silvio Bicciato. 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 Silvio Bicciato. The network helps show where Silvio Bicciato may publish in the future.
Co-authorship network of co-authors of Silvio Bicciato
This figure shows the co-authorship network connecting the top 25 collaborators of Silvio Bicciato. A scholar is included among the top collaborators of Silvio Bicciato 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 Silvio Bicciato. Silvio Bicciato is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 4 | |
| 3 | 3 | |
| 4 | 11 | |
| 5 | 11 | |
| 6 | 16 | |
| 7 | YAP/TAZ activity in stromal cells prevents ageing by controlling cGAS–STINGbreakdown → | 184 |
| 8 | 17 | |
| 9 | 3 | |
| 10 | 7 | |
| 11 | 27 | |
| 12 | 46 | |
| 13 | 20 | |
| 14 | 157 | |
| 15 | 146 | |
| 16 | 2 | |
| 17 | 44 | |
| 18 | 38 | |
| 19 | A Batch-Type System for Large-Scale Solid-Phase Oligonucleotide Synthesis | 1 |
| 20 | Development of a Prototype for the Automated Solid-Phase Synhtesis of Peptides | 1 |
About Silvio Bicciato
Silvio Bicciato is a scholar working on Biological Psychiatry, Cancer Research and Molecular Biology, having authored 181 papers that have together received 19.0k indexed citations. Recurring topics across this work include Hippo pathway signaling and YAP/TAZ (21 papers), Gene expression and cancer classification (19 papers) and Genomics and Chromatin Dynamics (17 papers). The work is most often cited by research in Cell Biology (7.1k citations), Biological Psychiatry (421 citations) and Cancer Research (2.5k citations). Silvio Bicciato has collaborated with scholars based in Italy, United States and United Kingdom. Frequent co-authors include Mattia Forcato, Michelangelo Cordenonsi, Stefano Piccolo, Francesca Zanconato, Sirio Dupont, Elena Enzo, Mariaceleste Aragona, Stefano Giulitti, Leonardo Morsut and Jimmy Le Digabel. Their work appears in journals such as Nature, Cell and Nucleic Acids 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.