Patrizio Di Micco
- Biotechnology top 10%
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- RNA and protein synthesis mechanisms 7
- RNA modifications and cancer 5
- Mitochondrial Function and Pathology 4
- Bioinformatics and Genomic Networks 3
- Protein Structure and Dynamics 2
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- Computational Drug Discovery Methods 6
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- Monoclonal and Polyclonal Antibodies Research 3
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- Advanced Proteomics Techniques and Applications 2
- Co-authors
- Veronica MoreaBissan Al‐LazikaniCostas MitsopoulosAlbert A. AntolínPaul WorkmanBuğra ÖzerChristos KannasElizabeth A. Coker
- Journals
- Nucleic Acids Research (4 papers)Scientific Reports (2 papers)Human Molecular Genetics (2 papers)
- Partner nations
- ItalyUnited KingdomUnited States
In The Last Decade
Patrizio Di Micco
20 papers receiving 589 citations
Peers
Comparison fields: 5 of 81
- Biotechnology 60
- Molecular Biology 448
- Clinical Biochemistry 32
- Biomaterials 60
- Aging 8
Countries citing papers authored by Patrizio Di Micco
This map shows the geographic impact of Patrizio Di Micco'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 Patrizio Di Micco with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Patrizio Di Micco more than expected).
Fields of papers citing papers by Patrizio Di Micco
This network shows the impact of papers produced by Patrizio Di Micco. 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 Patrizio Di Micco. The network helps show where Patrizio Di Micco may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Patrizio Di Micco, 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 | 2025 | 0 | |
| 2 | 2024 | 2 | |
| 3 | 2022 | 7 | |
| 4 | 2022 | 19 | |
| 5 | 2021 | 16 | |
| 6 | 2020 | 64 | |
| 7 | 2020 | 9 | |
| 8 | 2018 | 54 | |
| 9 | 2018 | 4 | |
| 10 | 2018 | 1 | |
| 11 | 2017 | 9 | |
| 12 | 2015 | 19 | |
| 13 | 2015 | 18 | |
| 14 | 2014 | 6 | |
| 15 | 2014 | 37 | |
| 16 | 2014 | 37 | |
| 17 | 2012 | 85 | |
| 18 | 2012 | 63 | |
| 19 | 2011 | 55 | |
| 20 | 2011 | 8 |
About Patrizio Di Micco
Patrizio Di Micco is a scholar working on Aging, Computational Theory and Mathematics and Molecular Biology, having authored 21 papers that have together received 595 indexed citations. Recurring topics across this work include RNA and protein synthesis mechanisms (7 papers), Computational Drug Discovery Methods (6 papers), RNA modifications and cancer (5 papers), Mitochondrial Function and Pathology (4 papers), Bioinformatics and Genomic Networks (3 papers), Monoclonal and Polyclonal Antibodies Research (3 papers), Protein Structure and Dynamics (2 papers) and Advanced Proteomics Techniques and Applications (2 papers). The work is most often cited by research in Biotechnology (60 citations), Molecular Biology (448 citations) and Clinical Biochemistry (32 citations). Patrizio Di Micco has collaborated with scholars based in Italy, United Kingdom and United States. Frequent co-authors include Veronica Morea, Bissan Al‐Lazikani, Costas Mitsopoulos, Albert A. Antolín, Paul Workman, Buğra Özer, Christos Kannas, Elizabeth A. Coker, Pierpaolo Ceci and Elisabetta Falvo. Their work appears in journals such as Nucleic Acids Research, Scientific Reports, Human Molecular Genetics, Molecular Cancer Therapeutics and JCO Clinical Cancer Informatics.
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.