Roberto Mosca

4.1k citations
23 papers · 1.7k indexed · h-index 17

Roberto Mosca

23 papers receiving 1.6k citations

Peers

Roberto Mosca
Comparison fields: 5 of 118
  • Computational Theory and Mathematics 358
  • Molecular Biology 1.4k
  • Cell Biology 152
  • Genetics 169
  • Materials Chemistry 236
Replace Karim M. ElSawy with:
Karim M. ElSawy United Kingdom
Arnaud Céol Italy
Xin‐Qiu Yao United States
Dawei Lin United States
David T. Barkan United States
Nurcan Tunçbağ Türkiye
Anatoly Sorokin Russia
Inbal Halperin United States
Donald Petrey United States
Thomas Madej United States
Roberto Mosca relative to Karim M. ElSawy United Kingdom Karim M. ElSawy's profile →
Citations per field
00.5×1.6×
Karim M. ElSawy · 1×
Citations per year

Countries citing papers authored by Roberto Mosca

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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-authorship network

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.

Border = papers with Roberto Mosca Line = papers co-authored together Roberto Mosca links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 201921
2 20174
3 201629
4 20152
5 201545
6 201443
7 201426
8 2014172
9 201334
10 201377
11 2013185
12 201248
13 2012326
14 201181
15 2010238
16 200961
17 200988
18 200841
19 20083
20 200893

About Roberto Mosca

Roberto Mosca is a scholar working on Molecular Biology, Critical Care and Intensive Care Medicine, Computational Theory and Mathematics, Genetics and Emergency Medicine, having authored 23 papers that have together received 1.7k indexed citations. Recurring topics across this work include Bioinformatics and Genomic Networks (12 papers), Protein Structure and Dynamics (8 papers), Microbial Metabolic Engineering and Bioproduction (8 papers), Computational Drug Discovery Methods (3 papers), Genomics and Phylogenetic Studies (3 papers), Fungal and yeast genetics research (2 papers), Enzyme Structure and Function (2 papers) and Genomics and Rare Diseases (1 paper). The work is most often cited by research in Computational Theory and Mathematics (358 citations), Molecular Biology (1.4k citations), Cell Biology (152 citations), Genetics (169 citations) and Materials Chemistry (236 citations). Roberto Mosca has collaborated with scholars based in Spain, United States and Italy. Frequent co-authors include Patrick Aloy, Arnaud Céol, Amelie Stein, Judith Farrés, Albert Pujol, T. Schneider, Roger Olivella, Miquel Duran‐Frigola, Carles Pons and Roland A. Pache. Their work appears in journals such as Nucleic Acids Research, Molecular & Cellular Proteomics, Structure, Interactive Cardiovascular and Thoracic Surgery and Current Opinion in Structural 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.

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