Marc O’Reilly

2.7k citations
27 papers · 2.2k · h-index 18

Impact in

Papers in

Marc O’Reilly

26 papers receiving 2.1k citations

Peers

Marc O’Reilly
Comparison fields: 5 of 82
  • Computational Theory and Mathematics 497
  • Cancer Research 385
  • Organic Chemistry 393
  • Molecular Biology 707
  • Oncology 191
Replace Alexander G. Pavlovsky with:
Alexander G. Pavlovsky United States
N.O. Concha United States
Gabriele Fendrich Switzerland
Bi‐Ching Sang Japan
Jean‐Michel Rondeau Switzerland
Nino Campobasso United States
John W. Cuozzo United States
Zenon D. Konteatis United States
Chang H. Park United States
Guixian Jin United States
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Citations per field
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Alexander G. Pavlovsky · 1×
Citations per year

Countries citing papers authored by Marc O’Reilly

Since Specialization
Citations

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

Fields of papers citing papers by Marc O’Reilly

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Marc O’Reilly. 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 Marc O’Reilly. The network helps show where Marc O’Reilly may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 27 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2012549
2 2008314
3 2008292
4 2009192
5 2004162
6 199694
7 201079
8 201978
9 201362
10 199756
11 201853
12 199949
13 201239
14 199926
15 202125
16 201924
17 202222
18 201620
19 202118
20 201415

About Marc O’Reilly

Marc O’Reilly is a scholar working on Computational Theory and Mathematics, Organic Chemistry, Molecular Biology, Materials Chemistry and Cancer Research, having authored 27 papers that have together received 2.2k indexed citations. Recurring topics across this work include Enzyme Structure and Function (6 papers), Computational Drug Discovery Methods (6 papers), Melanoma and MAPK Pathways (5 papers), Protein Kinase Regulation and GTPase Signaling (4 papers), Synthesis and biological activity (4 papers), Cancer, Hypoxia, and Metabolism (2 papers), Click Chemistry and Applications (2 papers) and Carbohydrate Chemistry and Synthesis (2 papers). The work is most often cited by research in Computational Theory and Mathematics (497 citations), Cancer Research (385 citations), Organic Chemistry (393 citations), Molecular Biology (707 citations) and Oncology (191 citations). Marc O’Reilly has collaborated with scholars based in United Kingdom, Germany and Netherlands. Frequent co-authors include Louise Napier Johnson, Finn P. Holding, Petra Hillmann, Barbara Chaneton, Liang Zheng, Karen H. Vousden, Christian Frezza, Andris Jankevics, Eyal Gottlieb and Joseph E. Coyle. Their work appears in journals such as Journal of Medicinal Chemistry, Molecular Cancer Therapeutics, Structure, Current Opinion in Structural Biology and Nature Structural & Molecular Biology.

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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