Richard D. Taylor

8.8k citations
28 papers · 7.0k indexed · 4 hit papers · h-index 18

Richard D. Taylor

28 papers receiving 6.8k citations

Hit Papers

Improved protein–ligand docking using GOLD2002202620102018200320142002202250010001.5k2.0k

Peers

Richard D. Taylor
Comparison fields: 5 of 140
  • Molecular Biology 3.4k
  • Organic Chemistry 3.0k
  • Computational Theory and Mathematics 2.1k
  • Pharmacology 584
  • Materials Chemistry 526
Replace György M. Keserű with:
György M. Keserű Hungary
Christine Humblet United States
Wayne C. Guida United States
Arup K. Ghose United States
Vellarkad N. Viswanadhan United States
Peter Ertl Switzerland
Weiliang Zhu China
José L. Medina‐Franco Mexico
George Chang United States
Stefano Forli United States
Richard D. Taylor relative to György M. Keserű Hungary György M. Keserű's profile →
Citations per field
00.5×1.5×
György M. Keserű · 1×
Citations per year

Countries citing papers authored by Richard D. Taylor

Since Specialization
Citations

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

Fields of papers citing papers by Richard D. Taylor

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Richard D. Taylor. 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 Richard D. Taylor. The network helps show where Richard D. Taylor may publish in the future.

Co-authorship network of co-authors of Richard D. Taylor

This figure shows the co-authorship network connecting the top 25 collaborators of Richard D. Taylor. A scholar is included among the top collaborators of Richard D. Taylor based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Richard D. Taylor. Richard D. Taylor is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 5
2 4
3 17
4 8
5 43
6 36
7 30
8 53
9
Rings in Drugsbreakdown →
2051
10 15
11 275
12 86
13 10
14 327
15 63
16
Improved protein–ligand docking using GOLDbreakdown →
2421
17
A review of protein-small molecule docking methodsbreakdown →
483
18 318
19 14
20 15

About Richard D. Taylor

Richard D. Taylor is a scholar working on Computational Theory and Mathematics, Pharmacology and Radiology, Nuclear Medicine and Imaging, having authored 28 papers that have together received 7.0k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (16 papers), Protein Structure and Dynamics (10 papers) and Monoclonal and Polyclonal Antibodies Research (7 papers). The work is most often cited by research in Computational Theory and Mathematics (2.1k citations), Organic Chemistry (3.0k citations) and Molecular Biology (3.4k citations). Richard D. Taylor has collaborated with scholars based in United Kingdom, United States and Belgium. Frequent co-authors include Alastair D. G. Lawson, Malcolm MacCoss, Christopher W. Murray, Marcel L. Verdonk, Michael J. Hartshorn, Jason C. Cole, Jonathan W. Essex, Philip J. Jewsbury, Robin Taylor and J. Willem M. Nissink. Their work appears in journals such as Chemical Society Reviews, Scientific Reports and Monthly Notices of the Royal Astronomical Society.

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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