Brian Dymock

77 papers receiving 2.8k citations

Peers

Brian Dymock
Comparison fields: 5 of 104
  • Biochemistry 303
  • Computational Theory and Mathematics 502
  • Genetics 320
  • Molecular Biology 1.8k
  • Organic Chemistry 553
Replace K. Huber with:
K. Huber United Kingdom
Stefania Sarno Italy
A. Chaikuad Germany
Evripidis Gavathiotis United States
Joseph M. Salvino United States
Jennifer S. Carew United States
Jonathan M. Elkins United Kingdom
Luciana Marinelli Italy
Haitao Ji United States
Akane Kawamura United Kingdom
Brian Dymock relative to K. Huber United Kingdom K. Huber's profile →
Citations per field
00.5×3.0×
K. Huber · 1×
Citations per year

Countries citing papers authored by Brian Dymock

Since Specialization
Citations

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

Fields of papers citing papers by Brian Dymock

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 78 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2004210
2 2005177
3 2011152
4 2011149
5 2011105
6 201599
7 201792
8 200491
9 201682
10 201178
11 201375
12 201572
13 200667
14 200566
15 201565
16 200661
17 201761
18 200157
19 201654
20 200054

About Brian Dymock

Brian Dymock is a scholar working on Biochemistry, Genetics, Computational Theory and Mathematics, Molecular Biology and Oncology, having authored 78 papers that have together received 2.9k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (12 papers), Heat shock proteins research (11 papers), Histone Deacetylase Inhibitors Research (10 papers), Cytokine Signaling Pathways and Interactions (9 papers), Myeloproliferative Neoplasms: Diagnosis and Treatment (9 papers), Sulfur Compounds in Biology (9 papers), Protein Degradation and Inhibitors (6 papers) and Chronic Lymphocytic Leukemia Research (6 papers). The work is most often cited by research in Biochemistry (303 citations), Computational Theory and Mathematics (502 citations), Genetics (320 citations), Molecular Biology (1.8k citations) and Organic Chemistry (553 citations). Brian Dymock has collaborated with scholars based in Singapore, United Kingdom and United States. Frequent co-authors include Philip K. Moore, Anders Poulsen, Martin J. Drysdale, Xavier Barril, Paul Workman, A.E. Surgenor, Haishan Wang, Feng Wei, Lisa Wright and Anthony D. William. Their work appears in journals such as Bioorganic & Medicinal Chemistry Letters, Journal of Medicinal Chemistry, European Journal of Medicinal Chemistry, Expert Opinion on Therapeutic Patents and Future Medicinal Chemistry.

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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