Michele Di Mascio

4.8k citations
66 papers · 3.6k indexed · h-index 32

Michele Di Mascio

65 papers receiving 3.5k citations

Peers

Michele Di Mascio
Comparison fields: 5 of 118
  • Virology 1.4k
  • Orthopedics and Sports Medicine 848
  • Infectious Diseases 913
  • Cellular and Molecular Neuroscience 809
  • Immunology 551
Replace Takeshi Nishijima with:
Takeshi Nishijima Japan
Abhijit Chaudhuri United Kingdom
Jennifer Hammond United States
Qing Gao China
Elyse J. Singer United States
David Shurtleff United States
Sudesh Prabhakar India
Rasha Hammamieh United States
Debra Johnson United States
Aarti Gautam United States
Michele Di Mascio relative to Takeshi Nishijima Japan Takeshi Nishijima's profile →
Citations per field
00.5×10×15×21.7×
Takeshi Nishijima · 1×
Citations per year

Countries citing papers authored by Michele Di Mascio

Since Specialization
Citations

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

Fields of papers citing papers by Michele Di Mascio

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20250
2 20201
3 201912
4 201920
5
Can Modern Trends in Elite Football Match Demands Be Translated into Novel Training and Testing Modes?
20183
6 20189
7 20183
8 20164
9 201613
10 20154
11 2012100
12 201275
13 201014
14 2010336
15 20094
16 20041
17 200369
18 200030
19 199924
20 1999167

About Michele Di Mascio

Michele Di Mascio is a scholar working on Virology, Infectious Diseases, Orthopedics and Sports Medicine, Biological Psychiatry and Immunology, having authored 66 papers that have together received 3.6k indexed citations. Recurring topics across this work include HIV Research and Treatment (33 papers), HIV/AIDS drug development and treatment (15 papers), HIV/AIDS Research and Interventions (14 papers), Immune Cell Function and Interaction (12 papers), Sports Performance and Training (8 papers), Neurotransmitter Receptor Influence on Behavior (8 papers), Sports injuries and prevention (7 papers) and Neural dynamics and brain function (6 papers). The work is most often cited by research in Virology (1.4k citations), Orthopedics and Sports Medicine (848 citations), Infectious Diseases (913 citations), Cellular and Molecular Neuroscience (809 citations) and Immunology (551 citations). Michele Di Mascio has collaborated with scholars based in United States, Italy and United Kingdom. Frequent co-authors include Giuseppe Di Giovanni, Vincenzo Di Matteo, Paul S. Bradley, Alan S. Perelson, David D. Ho, Daniel J. Peart, Ennio Esposito, Martin Markowitz, Michael J. Louie and Arlene Hurley. Their work appears in journals such as Journal of Virology, Blood, Neuroscience, The Journal of Strength and Conditioning Research and Archives of Gerontology and Geriatrics.

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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