Mark Mackey

1.4k citations
19 papers · 980 · h-index 11

Impact in

Papers in

Mark Mackey

18 papers receiving 940 citations

Peers

Mark Mackey
Comparison fields: 5 of 117
  • Computational Theory and Mathematics 439
  • Molecular Biology 590
  • Pharmacology 103
  • Organic Chemistry 168
  • Physical and Theoretical Chemistry 47
Replace Alfonso T. García‐Sosa with:
Alfonso T. García‐Sosa Estonia
Trung Hai Nguyen Vietnam
Sayan Mondal United States
Delaram Ghoreishi United States
John Marelius Sweden
Miriam Sgobba Italy
Kunqian Yu China
Mark McGann United States
Scott P. Brown United States
Changge Ji China
Mark Mackey relative to Alfonso T. García‐Sosa Estonia Alfonso T. García‐Sosa's profile →
Citations per field
00.5×1.5×
Alfonso T. García‐Sosa · 1×
Citations per year

Countries citing papers authored by Mark Mackey

Since Specialization
Citations

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

Fields of papers citing papers by Mark Mackey

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

19 of 19 papers shown
#Work
1 2006311
2 2020149
3 2019122
4 200895
5 200759
6 200948
7 201345
8 202038
9 202235
10 201128
11 202324
12 20226
13 20025
14 20045
15 20254
16 20143
17 20022
18 20081
19 20250

About Mark Mackey

Mark Mackey is a scholar working on Molecular Biology, Computational Theory and Mathematics, Materials Chemistry, Computer Networks and Communications and Pharmacology, having authored 19 papers that have together received 980 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (13 papers), Protein Structure and Dynamics (7 papers), Machine Learning in Materials Science (3 papers), Chemical Synthesis and Analysis (3 papers), Microbial Natural Products and Biosynthesis (2 papers), Parallel Computing and Optimization Techniques (2 papers), Bioinformatics and Genomic Networks (2 papers) and Enzyme Structure and Function (2 papers). The work is most often cited by research in Computational Theory and Mathematics (439 citations), Molecular Biology (590 citations), Pharmacology (103 citations), Organic Chemistry (168 citations) and Physical and Theoretical Chemistry (47 citations). Mark Mackey has collaborated with scholars based in United Kingdom, United States and Italy. Frequent co-authors include Andy Vinter, Sally Rose, Matthias R. Bauer, James L. Melville, Julien Michel, Paolo Tosco, Antonia S. J. S. Mey, Jeremy G. Vinter, Stuart Firth‐Clark and Maximilian Kühn. Their work appears in journals such as Journal of Chemical Information and Modeling, ACS Medicinal Chemistry Letters, Journal of the American Chemical Society, Journal of Medicinal Chemistry and Expert Opinion on Drug Discovery.

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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