M. Sacco

2.4k citations
18 papers · 1.5k indexed · 1 hit paper · h-index 12
Topics
SARS-CoV-2 and COVID-19 Research (7 papers)Computational Drug Discovery Methods (7 papers)Bacterial Genetics and Biotechnology (5 papers)

In The Last Decade

M. Sacco

17 papers receiving 1.5k citations

Hit Papers

Boceprevir, GC-376, and calpain inhibitors II, XII inhibi...20202026202220242020200400600

Peers

M. Sacco
Comparison fields: 5 of 83
  • Infectious Diseases 915
  • Computational Theory and Mathematics 907
  • Molecular Biology 461
  • Organic Chemistry 321
  • Epidemiology 93
Replace Reaz Uddin with:
Reaz Uddin Pakistan
R. Jedrzejczak United States
Peter B. Madrid United States
Katharina Rox Germany
Muhammad Usman Mirza Pakistan
Priyanka Sharma India
Sumra Wajid Abbasi Pakistan
Keqiang Fan China
Kiira Ratia United States
Jane X. Kelly United States
M. Sacco relative to Reaz Uddin Pakistan Reaz Uddin's profile →
Citations per field
00.5×1.5×2.3×
Reaz Uddin · 1×
Citations per year

Countries citing papers authored by M. Sacco

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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 of co-authors of M. Sacco

This figure shows the co-authorship network connecting the top 25 collaborators of M. Sacco. A scholar is included among the top collaborators of M. Sacco 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 M. Sacco. M. Sacco is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

18 of 18 papers shown
#WorkIndexed citations
1 5
2 18
3 2
4 18
5 19
6 3
7 112
8 106
9 143
10 63
11 6
12
Boceprevir, GC-376, and calpain inhibitors II, XII inhibit SARS-CoV-2 viral replication by targeting the viral main proteasebreakdown →
616
13 284
14 16
15 49
16 23
17 8
18 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) and Bacterial Genetics and Biotechnology (5 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.

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