Suzanne Brewerton

2.5k citations
21 papers · 1.3k · 1 hit paper · h-index 12

Impact in

Papers in

Suzanne Brewerton

21 papers receiving 1.3k citations

Suzanne Brewerton's Hit Papers

Diverse, High-Quality Test Set for the Validation of Protein−Ligand Docking Performance 2007 · 528 citations
5280+6+12Years since publication100200300400500

Peers

Suzanne Brewerton
Comparison fields: 5 of 118
  • Computational Theory and Mathematics 509
  • Molecular Biology 864
  • Pharmacology 117
  • Genetics 131
  • Pharmacology 38
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Peter M.U. Ung United States
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Citations per field
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Citations per year

Countries citing papers authored by Suzanne Brewerton

Since Specialization
Citations

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

Fields of papers citing papers by Suzanne Brewerton

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 21 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Diverse, High-Quality Test Set for the Validation of Protein−Ligand Docking Performance
Hit paper breakdown →
2007528
2 2016212
3 2006144
4 201399
5 201797
6
The use of protein-ligand interaction fingerprints in docking.
200849
7 200324
8 200324
9 201423
10 200521
11 201416
12 201312
13 202411
14 200811
15 201210
16 20178
17 20078
18 20156
19 20134
20 20141

About Suzanne Brewerton

Suzanne Brewerton is a scholar working on Molecular Biology, Computational Theory and Mathematics, Pharmacology, Cellular and Molecular Neuroscience and Materials Chemistry, having authored 21 papers that have together received 1.3k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (10 papers), Protein Structure and Dynamics (4 papers), Enzyme Structure and Function (3 papers), Alzheimer's disease research and treatments (2 papers), Neuroscience and Neuropharmacology Research (2 papers), Metabolomics and Mass Spectrometry Studies (2 papers), Receptor Mechanisms and Signaling (2 papers) and Bioinformatics and Genomic Networks (2 papers). The work is most often cited by research in Computational Theory and Mathematics (509 citations), Molecular Biology (864 citations), Pharmacology (117 citations), Genetics (131 citations) and Pharmacology (38 citations). Suzanne Brewerton has collaborated with scholars based in United Kingdom, United States and Belgium. Frequent co-authors include Gianni Chessari, Michael J. Hartshorn, Marcel L. Verdonk, Wijnand T. M. Mooij, Paul N. Mortenson, Christopher W. Murray, Tom L. Blundell, Ewen F. Kirkness, Amalio Telenti and William Biggs. Their work appears in journals such as Proceedings of the National Academy of Sciences, Bioinformatics, ACS Chemical Biology, Chemical Science and Combinatorial Chemistry & High Throughput Screening.

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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