Michele Fratello

1.4k citations
35 papers · 719 indexed · 1 hit paper · h-index 15
Topics
Bioinformatics and Genomic Networks (13 papers)Gene expression and cancer classification (12 papers)Computational Drug Discovery Methods (9 papers)
Partner nations
FinlandItalySweden

In The Last Decade

Michele Fratello

32 papers receiving 703 citations

Hit Papers

Advances in De Novo Drug Design: From Conventional to Mac...2021202620222024202150100150200

Peers

Michele Fratello
Comparison fields: 5 of 117
  • Molecular Biology 328
  • Computational Theory and Mathematics 257
  • Materials Chemistry 95
  • Neurology 76
  • Psychiatry and Mental health 46
Replace Daniel Domingo‐Fernándéz with:
Daniel Domingo‐Fernándéz Germany
Jielin Xu United States
Erfan Younesi Germany
Emile F. Nuwaysir United States
Alpha Tom Kodamullil Germany
Marek Ostaszewski Luxembourg
J.B. Brown Japan
Nathan Johnson United States
Marie‐Pier Scott‐Boyer Canada
Xiao Gan United States
Michele Fratello relative to Daniel Domingo‐Fernándéz Germany Daniel Domingo‐Fernándéz's profile →
Citations per field
00.5×10×15.8×
Daniel Domingo‐Fernándéz · 1×
Citations per year

Countries citing papers authored by Michele Fratello

Since Specialization
Citations

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

Fields of papers citing papers by Michele Fratello

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Michele Fratello

This figure shows the co-authorship network connecting the top 25 collaborators of Michele Fratello. A scholar is included among the top collaborators of Michele Fratello based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Michele Fratello. Michele Fratello is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 1
2 0
3 4
4 22
5 13
6 1
7 5
8 14
9 2
10 0
11 8
12 8
13 11
14 35
15 36
16 23
17 42
18 5
19 45
20 7

About Michele Fratello

Michele Fratello is a scholar working on Computational Theory and Mathematics, Biophysics and Sensory Systems, having authored 35 papers that have together received 719 indexed citations. Recurring topics across this work include Bioinformatics and Genomic Networks (13 papers), Gene expression and cancer classification (12 papers) and Computational Drug Discovery Methods (9 papers). The work is most often cited by research in Computational Theory and Mathematics (257 citations), Health Informatics (8 citations) and Neurology (76 citations). Michele Fratello has collaborated with scholars based in Finland, Italy and Sweden. Frequent co-authors include Angela Serra, Dario Greco, Antreas Afantitis, Georgia Melagraki, Anastasios G. Papadiamantis, Varnavas D. Mouchlis, Vassilis Aidinis, Iseult Lynch, Roberto Tagliaferri and Fabrizio Esposito. Their work appears in journals such as Bioinformatics, International Journal of Molecular Sciences and BMC Bioinformatics.

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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