Matthew G. Rees

11.1k citations
38 papers · 791 · h-index 15

Impact in

Papers in

    • Metabolism, Diabetes, and Cancer 7
    • Protein Degradation and Inhibitors 4
    • Epigenetics and DNA Methylation 3
    • Bioinformatics and Genomic Networks 3
    • Ubiquitin and proteasome pathways 3
    • Melanoma and MAPK Pathways 2
    • Pancreatic function and diabetes 8

Matthew G. Rees

34 papers receiving 781 citations

Peers

Matthew G. Rees
Comparison fields: 5 of 121
  • Endocrinology, Diabetes and Metabolism 108
  • Molecular Biology 389
  • Cancer Research 72
  • Biomaterials 57
  • Human-Computer Interaction 23
Replace Laura Lentini with:
Laura Lentini Italy
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Shuo Yang China
Diane Marotta United States
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Chuang Chen China
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Citations per field
00.5×3.2×
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Citations per year

Countries citing papers authored by Matthew G. Rees

Since Specialization
Citations

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

Fields of papers citing papers by Matthew G. Rees

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Matthew G. Rees. 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 Matthew G. Rees. The network helps show where Matthew G. Rees may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 38 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2022136
2 201590
3 201174
4
Chemistry and structure activity relationships of bafilomycin A1, a potent and selective inhibitor of the vacuolar H+-ATPase.
199966
5 202165
6 202349
7 201337
8 201136
9 201536
10 202335
11 202225
12 201221
13 202319
14 201419
15 201218
16 200210
17 20229
18 20229
19 20016
20 20145

About Matthew G. Rees

Matthew G. Rees is a scholar working on Molecular Biology, Surgery, Genetics, Genetics and Oncology, having authored 38 papers that have together received 791 indexed citations. Recurring topics across this work include Pancreatic function and diabetes (8 papers), Metabolism, Diabetes, and Cancer (7 papers), Protein Degradation and Inhibitors (4 papers), Epigenetics and DNA Methylation (3 papers), Bioinformatics and Genomic Networks (3 papers), Ubiquitin and proteasome pathways (3 papers), Melanoma and MAPK Pathways (2 papers) and Endoplasmic Reticulum Stress and Disease (2 papers). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (108 citations), Molecular Biology (389 citations), Cancer Research (72 citations), Biomaterials (57 citations) and Human-Computer Interaction (23 citations). Matthew G. Rees has collaborated with scholars based in United States, United Kingdom and Austria. Frequent co-authors include Anna L. Gloyn, Anne Raimondo, Jennifer A. Roth, Stefania Gagliardi, C Farina, Francis S. Collins, Melissa M. Ronan, Nicola L. Beer, Simone Baltrusch and Jaime H. Cheah. Their work appears in journals such as Nature Chemical Biology, Molecular Cancer Therapeutics, Journal of the American Chemical Society, Cancer Research and Nature Metabolism.

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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