Roberto Mosca
Impact in
- Molecular Biology top 5%
- Bioinformatics and Genomic Networks
- Protein Structure and Dynamics
-
- Computational Drug Discovery Methods
Papers in
-
- Bioinformatics and Genomic Networks 11
- Protein Structure and Dynamics 8
- Genomics and Chromatin Dynamics 1
- Fractal and DNA sequence analysis 1
- Genetics 4
- Bacterial Genetics and Biotechnology 2
- Co-authors
- Patrick Aloy (18 shared papers)Arnaud Gerard Michel Ceol (6 shared papers)Amelie Stein (2 shared papers)Judith Farrés (1 shared paper)Roger Olivella (2 shared papers)Miquel Duran‐Frigola (3 shared papers)Roland A. Pache (1 shared paper)Alfonso Valencia (1 shared paper)
- Journals
- Nucleic Acids Research (3 papers)Nature Methods (2 papers)Molecular Systems Biology (2 papers)Structure (2 papers)Molecular & Cellular Proteomics (2 papers)
- Partner nations
- SpainUnited StatesItaly
In The Last Decade
Roberto Mosca
25 papers receiving 3k citations
Roberto Mosca's Hit Papers
Peers
Comparison fields: 5 of 115
- Molecular Biology 2.1k
- Computational Theory and Mathematics 310
- Cell Biology 177
- Genetics 309
- Spectroscopy 163
Countries citing papers authored by Roberto Mosca
This map shows the geographic impact of Roberto Mosca'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 Mosca with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Roberto Mosca more than expected).
Fields of papers citing papers by Roberto Mosca
This network shows the impact of papers produced by Roberto Mosca. 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 Mosca. The network helps show where Roberto Mosca may publish in the future.
Co-authors
The 25 scholars most cited alongside Roberto Mosca, 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 25 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | A Proteome-Scale Map of the Human Interactome Network Hit paper breakdown → | 2014 | 1067 |
| 2 | 2012 | 366 | |
| 3 | 2010 | 272 | |
| 4 | 2013 | 214 | |
| 5 | 2014 | 188 | |
| 6 | 2009 | 93 | |
| 7 | 2008 | 92 | |
| 8 | 2016 | 87 | |
| 9 | 2011 | 83 | |
| 10 | 2013 | 80 | |
| 11 | 2015 | 78 | |
| 12 | 2009 | 62 | |
| 13 | 2012 | 50 | |
| 14 | 2014 | 49 | |
| 15 | 2015 | 48 | |
| 16 | 2008 | 41 | |
| 17 | 2013 | 41 | |
| 18 | 2016 | 39 | |
| 19 | 2016 | 32 | |
| 20 | 2014 | 30 |
About Roberto Mosca
Roberto Mosca is a scholar working on Molecular Biology, Genetics, Cell Biology, Computational Theory and Mathematics and Cancer Research, having authored 25 papers that have together received 3.1k indexed citations. Recurring topics across this work include Bioinformatics and Genomic Networks (11 papers), Protein Structure and Dynamics (8 papers), Bacterial Genetics and Biotechnology (2 papers), Enzyme Structure and Function (2 papers), Computational Drug Discovery Methods (2 papers), Microtubule and mitosis dynamics (1 paper), Genomics and Chromatin Dynamics (1 paper) and Fractal and DNA sequence analysis (1 paper). The work is most often cited by research in Molecular Biology (2.1k citations), Computational Theory and Mathematics (310 citations), Cell Biology (177 citations), Genetics (309 citations) and Spectroscopy (163 citations). Roberto Mosca has collaborated with scholars based in Spain, United States and Italy. Frequent co-authors include Patrick Aloy, Arnaud Gerard Michel Ceol, Amelie Stein, Judith Farrés, Roger Olivella, Miquel Duran‐Frigola, Roland A. Pache, Alfonso Valencia, Juan Fernández‐Recio and Tirso Pons. Their work appears in journals such as Nucleic Acids Research, Nature Methods, Molecular Systems Biology, Structure and Molecular & Cellular Proteomics.
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.