Simone Marini

68 papers receiving 1.5k citations

Hit Papers

Machine Learning Methods to Predict Diabetes Complications 2017 · 252 citations
252201720262020202350100150200250

Peers

Simone Marini
Comparison fields: 5 of 146
  • Health Information Management 190
  • Health Informatics 31
  • Reproductive Medicine 145
  • Molecular Medicine 47
  • Genetics 244
Replace Davood Bashash with:
Davood Bashash Iran
Tzu‐Hao Chang Taiwan
Xiaowei Zhan United States
Philipp E. Geyer Germany
Thangavel Alphonse Thanaraj Kuwait
Philippe Gain France
Miao Cui China
Haoming Xu China
Xiaoyi Chen China
John Kim United States
Simone Marini relative to Davood Bashash Iran Davood Bashash's profile →
Citations per field
00.5×5.6×
Davood Bashash · 1×
Citations per year

Countries citing papers authored by Simone Marini

Since Specialization
Citations

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

Fields of papers citing papers by Simone Marini

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Simone Marini, 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 Simone Marini Line = papers co-authored together Simone Marini links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 69 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2018330
2
Machine Learning Methods to Predict Diabetes Complications
Hit paper breakdown →
2017252
3 2018101
4 201894
5 202289
6 201945
7 201541
8 202039
9 201538
10 201334
11 201830
12 202030
13 201929
14 202027
15 202225
16 202025
17 202023
18 202022
19 199721
20 202017

About Simone Marini

Simone Marini is a scholar working on Molecular Medicine, Clinical Biochemistry, Virology, Infectious Diseases and Applied Microbiology and Biotechnology, having authored 69 papers that have together received 1.5k indexed citations. Recurring topics across this work include Genomics and Phylogenetic Studies (10 papers), Antibiotic Resistance in Bacteria (8 papers), vaccines and immunoinformatics approaches (7 papers), SARS-CoV-2 and COVID-19 Research (7 papers), Bioinformatics and Genomic Networks (6 papers), Heterotopic Ossification and Related Conditions (6 papers), Bacterial Identification and Susceptibility Testing (5 papers) and Mesenchymal stem cell research (4 papers). The work is most often cited by research in Health Information Management (190 citations), Health Informatics (31 citations), Reproductive Medicine (145 citations), Molecular Medicine (47 citations) and Genetics (244 citations). Simone Marini has collaborated with scholars based in United States, Italy and Japan. Frequent co-authors include Riccardo Bellazzi, Lucia Sacchi, Arianna Dagliati, Giulia Cogni, Valentina Tibollo, Marsida Teliti, Luca Chiovato, Pasquale De Cata, Jun Z. Li and Mattia Prosperi. Their work appears in journals such as Bioinformatics, Briefings in Bioinformatics, PLoS ONE, JMIR Public Health and Surveillance and Bone.

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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