M. Sacco
- Computational Theory and Mathematics top 0.5%
- Computational Drug Discovery Methods 7
- Infectious Diseases top 2%
- SARS-CoV-2 and COVID-19 Research 7
- Antimicrobial Resistance in Staphylococcus 3
- Molecular Medicine top 5%
- Antibiotic Resistance in Bacteria 4
- Organic Chemistry top 10%
- Pharmacology top 10%
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- Bacterial Genetics and Biotechnology 5
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- Bacterial biofilms and quorum sensing 4
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- interferon and immune responses 2
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- Bacteriophages and microbial interactions 2
- Co-authors
- Yu ChenJun WangChunlong MaYanmei HuJulia A. TownsendMichael T. MartyXiujun ZhangTommy Szeto
- Journals
- Journal of the American Chemical Society (1 paper)Nature Communications (1 paper)Scientific Reports (1 paper)
- Partner nations
- United StatesGreeceDenmark
In The Last Decade
M. Sacco
17 papers receiving 1.5k citations
Hit Papers
Peers
Comparison fields: 5 of 83
- Computational Theory and Mathematics 907
- Infectious Diseases 915
- Molecular Medicine 75
- Organic Chemistry 321
- Pharmacology 64
Countries citing papers authored by M. Sacco
This map shows the geographic impact of M. Sacco'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 M. Sacco with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites M. Sacco more than expected).
Fields of papers citing papers by M. Sacco
This network shows the impact of papers produced by M. Sacco. 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 M. Sacco. The network helps show where M. Sacco may publish in the future.
Co-authorship network
The 25 scholars most cited alongside M. Sacco, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2024 | 5 | |
| 2 | 2023 | 18 | |
| 3 | 2023 | 2 | |
| 4 | 2022 | 18 | |
| 5 | 2022 | 19 | |
| 6 | 2022 | 3 | |
| 7 | 2021 | 112 | |
| 8 | 2021 | 106 | |
| 9 | 2021 | 143 | |
| 10 | 2021 | 63 | |
| 11 | 2020 | 6 | |
| 12 | Boceprevir, GC-376, and calpain inhibitors II, XII inhibit SARS-CoV-2 viral replication by targeting the viral main proteasebreakdown → | 2020 | 616 |
| 13 | 2020 | 284 | |
| 14 | 2020 | 16 | |
| 15 | 2020 | 49 | |
| 16 | 2019 | 23 | |
| 17 | 2019 | 8 | |
| 18 | 2017 | 0 |
About M. Sacco
M. Sacco is a scholar working on Molecular Medicine, Infectious Diseases and Computational Theory and Mathematics, having authored 18 papers that have together received 1.5k indexed citations. Recurring topics across this work include SARS-CoV-2 and COVID-19 Research (7 papers), Computational Drug Discovery Methods (7 papers), Bacterial Genetics and Biotechnology (5 papers), Bacterial biofilms and quorum sensing (4 papers), Antibiotic Resistance in Bacteria (4 papers), Antimicrobial Resistance in Staphylococcus (3 papers), interferon and immune responses (2 papers) and Bacteriophages and microbial interactions (2 papers). The work is most often cited by research in Computational Theory and Mathematics (907 citations), Infectious Diseases (915 citations) and Molecular Medicine (75 citations). M. Sacco has collaborated with scholars based in United States, Greece and Denmark. Frequent co-authors include Yu Chen, Jun Wang, Chunlong Ma, Yanmei Hu, Julia A. Townsend, Michael T. Marty, Xiujun Zhang, Tommy Szeto, E. Bart Tarbet and Brett L. Hurst. Their work appears in journals such as Journal of the American Chemical Society, Nature Communications and Scientific Reports.
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.