Tito Panciera
- Cell Biology top 0.1%
- Molecular Biology top 2%
- Biomedical Engineering top 5%
- Oncology top 5%
- Physiology top 10%
- Co-authors
- Stefano PiccoloMichelangelo CordenonsiLuca AzzolinAntonio TotaroSirio DupontStefano GiulittiMariaceleste AragonaNicola Elvassore
- Topics
- Hippo pathway signaling and YAP/TAZ (17 papers)Cellular Mechanics and Interactions (11 papers)3D Printing in Biomedical Research (6 papers)
In The Last Decade
Tito Panciera
20 papers receiving 5.2k citations
Hit Papers
Peers
Comparison fields: 5 of 126
- Cell Biology 3.7k
- Molecular Biology 2.6k
- Biomedical Engineering 652
- Oncology 635
- Physiology 279
Countries citing papers authored by Tito Panciera
This map shows the geographic impact of Tito Panciera'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 Tito Panciera with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tito Panciera more than expected).
Fields of papers citing papers by Tito Panciera
This network shows the impact of papers produced by Tito Panciera. 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 Tito Panciera. The network helps show where Tito Panciera may publish in the future.
Co-authorship network of co-authors of Tito Panciera
This figure shows the co-authorship network connecting the top 25 collaborators of Tito Panciera. A scholar is included among the top collaborators of Tito Panciera 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 Tito Panciera. Tito Panciera 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 | 2 | |
| 3 | 3 | |
| 4 | YAP/TAZ activity in stromal cells prevents ageing by controlling cGAS–STINGbreakdown → | 184 |
| 5 | YAP/TAZ as master regulators in cancer: modulation, function and therapeutic approachesbreakdown → | 145 |
| 6 | 10 | |
| 7 | 25 | |
| 8 | 3 | |
| 9 | 88 | |
| 10 | 166 | |
| 11 | 50 | |
| 12 | 102 | |
| 13 | 219 | |
| 14 | YAP/TAZ upstream signals and downstream responsesbreakdown → | 709 |
| 15 | 3 | |
| 16 | 239 | |
| 17 | Mechanobiology of YAP and TAZ in physiology and diseasebreakdown → | 978 |
| 18 | 197 | |
| 19 | YAP/TAZ Incorporation in the β-Catenin Destruction Complex Orchestrates the Wnt Responsebreakdown → | 850 |
| 20 | A Mechanical Checkpoint Controls Multicellular Growth through YAP/TAZ Regulation by Actin-Processing Factorsbreakdown → | 1270 |
About Tito Panciera
Tito Panciera is a scholar working on Cell Biology, Biophysics and Biomedical Engineering, having authored 22 papers that have together received 5.2k indexed citations. Recurring topics across this work include Hippo pathway signaling and YAP/TAZ (17 papers), Cellular Mechanics and Interactions (11 papers) and 3D Printing in Biomedical Research (6 papers). The work is most often cited by research in Cell Biology (3.7k citations), Immunology and Allergy (237 citations) and Molecular Biology (2.6k citations). Tito Panciera has collaborated with scholars based in Italy, Germany and Hungary. Frequent co-authors include Stefano Piccolo, Michelangelo Cordenonsi, Luca Azzolin, Antonio Totaro, Sirio Dupont, Stefano Giulitti, Mariaceleste Aragona, Nicola Elvassore, Andrea Manfrin and Federica Michielin. Their work appears in journals such as Nature, 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.