Fabrizio Giordanetto
- Computational Theory and Mathematics top 0.5%
- Computational Drug Discovery Methods 19
- Molecular Biology top 2%
- Receptor Mechanisms and Signaling 8
- Protein Structure and Dynamics 6
- PI3K/AKT/mTOR signaling in cancer 5
- Biochemical and Molecular Research 4
- Organic Chemistry top 2%
- Click Chemistry and Applications 6
- Physiology top 2%
- Internal Medicine top 5%
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- Innovative Microfluidic and Catalytic Techniques Innovation 4
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- Chronic Lymphocytic Leukemia Research 4
Fabrizio Giordanetto
73 papers receiving 4.0k citations
Hit Papers
Peers
Comparison fields: 5 of 134
- Computational Theory and Mathematics 789
- Molecular Biology 2.7k
- Organic Chemistry 807
- Physiology 116
- Internal Medicine 88
Countries citing papers authored by Fabrizio Giordanetto
This map shows the geographic impact of Fabrizio Giordanetto'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 Fabrizio Giordanetto with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fabrizio Giordanetto more than expected).
Fields of papers citing papers by Fabrizio Giordanetto
This network shows the impact of papers produced by Fabrizio Giordanetto. 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 Fabrizio Giordanetto. The network helps show where Fabrizio Giordanetto may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Fabrizio Giordanetto, 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 | 2021 | 13 | |
| 2 | 2018 | 22 | |
| 3 | 2015 | 70 | |
| 4 | 2014 | 52 | |
| 5 | 2014 | 44 | |
| 6 | 2014 | 19 | |
| 7 | Oral Druggable Space beyond the Rule of 5: Insights from Drugs and Clinical Candidatesbreakdown → | 2014 | 555 |
| 8 | Structural basis of AMPK regulation by small molecule activatorsbreakdown → | 2013 | 428 |
| 9 | 2013 | 5 | |
| 10 | 2012 | 22 | |
| 11 | 2012 | 4 | |
| 12 | 2011 | 22 | |
| 13 | 2011 | 5 | |
| 14 | 2009 | 37 | |
| 15 | 2009 | 7 | |
| 16 | 2009 | 12 | |
| 17 | 2008 | 6 | |
| 18 | 2005 | 38 | |
| 19 | 2003 | 8 | |
| 20 | 2003 | 11 |
About Fabrizio Giordanetto
Fabrizio Giordanetto is a scholar working on Computational Theory and Mathematics, Molecular Biology and Physiology, having authored 73 papers that have together received 4.1k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (19 papers), Receptor Mechanisms and Signaling (8 papers), Protein Structure and Dynamics (6 papers), Click Chemistry and Applications (6 papers), PI3K/AKT/mTOR signaling in cancer (5 papers), Innovative Microfluidic and Catalytic Techniques Innovation (4 papers), Chronic Lymphocytic Leukemia Research (4 papers) and Biochemical and Molecular Research (4 papers). The work is most often cited by research in Computational Theory and Mathematics (789 citations), Molecular Biology (2.7k citations) and Organic Chemistry (807 citations). Fabrizio Giordanetto has collaborated with scholars based in Sweden, United Kingdom and Italy. Frequent co-authors include Jan Kihlberg, Björn Over, B.C. Doak, Guido Kroemer, Romano T. Kroemer, Frank Madeo, Nazanine Modjtahedi, Paul D. Lyne, Jin Li and Hongming Chen. Their work appears in journals such as Journal of the American Chemical Society, Nature Communications and Molecular Cell.
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.