Remo Calabrese

2.2k citations
8 papers · 1.6k indexed · 2 hit papers · h-index 5

Remo Calabrese

8 papers receiving 1.6k citations

Hit Papers

Functional annotations improve the predictive score of hu...5052006202620122019200400600

Peers

Remo Calabrese
Comparison fields: 5 of 89
  • Genetics 634
  • Molecular Biology 1.2k
  • Clinical Biochemistry 57
  • Cancer Research 118
  • Cell Biology 127
Replace Fuxiao Xin with:
Fuxiao Xin United States
Stefan Kammerer Germany
Marta Blumenfeld France
Martin Höhne Germany
Marie‐Claude Gingras United States
Evarist Planet Switzerland
J. Patrick Murphy Canada
Shuwei Li United States
Paul S. Meltzer United States
Remo Calabrese relative to Fuxiao Xin United States Fuxiao Xin's profile →
Citations per field
00.5×2.6×
Fuxiao Xin · 1×
Citations per year

Countries citing papers authored by Remo Calabrese

Since Specialization
Citations

This map shows the geographic impact of Remo Calabrese'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 Remo Calabrese with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Remo Calabrese more than expected).

Fields of papers citing papers by Remo Calabrese

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Remo Calabrese. 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 Remo Calabrese. The network helps show where Remo Calabrese may publish in the future.

Co-authorship network

The 6 scholars most cited alongside Remo Calabrese, 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 Remo Calabrese Line = papers co-authored together Remo Calabrese links everyone, so they are left out of the graph.

All Works

8 of 8 papers shown
#Work
1 2013252
2
Functional annotations improve the predictive score of human disease-related mutations in proteinsbreakdown →
2009505
3
Protein Folding, Misfolding and Diseases: The I-Mutant Suite
20092
4
Protein Folding, Misfolding and Diseases: The I-Mutant Suite
20081
5
Predicting the Insurgence of Human Genetic Diseases Due to Single Point Protein Mutation using Machine Learning Approach.
20071
6 20075
7
Predicting the insurgence of human genetic diseases associated to single point protein mutations with support vector machines and evolutionary informationbreakdown →
2006690
8 2005154

About Remo Calabrese

Remo Calabrese is a scholar working on Molecular Biology, Biotechnology and Genetics, having authored 8 papers that have together received 1.6k indexed citations. Recurring topics across this work include Machine Learning in Bioinformatics (5 papers), RNA and protein synthesis mechanisms (4 papers), Protein Structure and Dynamics (3 papers), Glycosylation and Glycoproteins Research (2 papers), Genomics and Rare Diseases (2 papers), Bioinformatics and Genomic Networks (2 papers), Ubiquitin and proteasome pathways (2 papers) and Peptidase Inhibition and Analysis (1 paper). The work is most often cited by research in Genetics (634 citations), Molecular Biology (1.2k citations) and Clinical Biochemistry (57 citations). Remo Calabrese has collaborated with scholars based in Italy and United States. Frequent co-authors include Rita Casadio, Emidio Capriotti, Piero Fariselli, Pier Luigi Martelli, Russ B. Altman and D.G. Mita.

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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