Roberto Serra
Impact in
- Genetics top 2%
- Chronic Lymphocytic Leukemia Research
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- Lymphoma Diagnosis and Treatment
Papers in
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- Complex Network Analysis Techniques 13
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- Origins and Evolution of Life 36
- Co-authors
- Marco Villani (115 shared papers)Roberto Vettor (22 shared papers)Roberto Fabris (19 shared papers)Salvatore Di Gregorio (11 shared papers)Stuart Alan Kauffman (19 shared papers)Alex Graudenzi (17 shared papers)Giovanni Federspil (8 shared papers)Annamaria Colacci (20 shared papers)
- Journals
- Journal of Theoretical Biology (5 papers)Blood (5 papers)Parallel Computing (3 papers)Life (3 papers)Journal of Computational Biology (2 papers)
- Partner nations
- ItalyUnited StatesNetherlands
In The Last Decade
Roberto Serra
205 papers receiving 4.9k citations
Peers
Comparison fields: 5 of 185
- Genetics 698
- Pathology and Forensic Medicine 768
- Molecular Biology 1.6k
- Physiology 535
- Computational Theory and Mathematics 374
Countries citing papers authored by Roberto Serra
This map shows the geographic impact of Roberto Serra'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 Roberto Serra with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Roberto Serra more than expected).
Fields of papers citing papers by Roberto Serra
This network shows the impact of papers produced by Roberto Serra. 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 Roberto Serra. The network helps show where Roberto Serra may publish in the future.
Co-authors
The 25 scholars most cited alongside Roberto Serra, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 218 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2012 | 380 | |
| 2 | 2012 | 313 | |
| 3 | 2006 | 260 | |
| 4 | 2017 | 213 | |
| 5 | 1999 | 170 | |
| 6 | 2014 | 153 | |
| 7 | 2020 | 143 | |
| 8 | 2004 | 124 | |
| 9 | 2013 | 111 | |
| 10 | 2013 | 109 | |
| 11 | 2020 | 109 | |
| 12 | 2007 | 102 | |
| 13 | 2004 | 100 | |
| 14 | 1990 | 94 | |
| 15 | 2006 | 87 | |
| 16 | 2010 | 82 | |
| 17 | 2013 | 80 | |
| 18 | 2001 | 72 | |
| 19 | 2005 | 72 | |
| 20 | 1998 | 71 |
About Roberto Serra
Roberto Serra is a scholar working on Statistical and Nonlinear Physics, Astronomy and Astrophysics, Molecular Biology, Computational Theory and Mathematics and Cellular and Molecular Neuroscience, having authored 218 papers that have together received 5.2k indexed citations. Recurring topics across this work include Gene Regulatory Network Analysis (70 papers), Origins and Evolution of Life (36 papers), Bioinformatics and Genomic Networks (29 papers), Cellular Automata and Applications (23 papers), Photoreceptor and optogenetics research (17 papers), Protein Structure and Dynamics (15 papers), Complex Network Analysis Techniques (13 papers) and Neural Networks and Applications (11 papers). The work is most often cited by research in Genetics (698 citations), Pathology and Forensic Medicine (768 citations), Molecular Biology (1.6k citations), Physiology (535 citations) and Computational Theory and Mathematics (374 citations). Roberto Serra has collaborated with scholars based in Italy, United States and Netherlands. Frequent co-authors include Marco Villani, Roberto Vettor, Roberto Fabris, Salvatore Di Gregorio, Stuart Alan Kauffman, Alex Graudenzi, Giovanni Federspil, Annamaria Colacci, G. Zanarini and Massimiliano Olivieri. Their work appears in journals such as Journal of Theoretical Biology, Blood, Parallel Computing, Life and Journal of Computational Biology.
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.