Randy J. Read

128.9k citations
197 papers · 86.9k indexed · 16 hit papers · h-index 69

Randy J. Read

193 papers receiving 86.3k citations

Hit Papers

Alpha...16819862026199920125.0k10.0k15.0k

Peers

Randy J. Read
Comparison fields: 5 of 187
  • Molecular Biology 62.2k
  • Structural Biology 1.1k
  • Endocrinology 2.7k
  • Biotechnology 4.3k
  • Cell Biology 7.9k
Replace Paul D. Adams with:
Paul D. Adams United States
Ralf W. Grosse‐Kunstleve United States
Paul Emsley United Kingdom
Kevin Cowtan United Kingdom
Airlie J. McCoy United Kingdom
Thomas C. Terwilliger United States
Jane S. Richardson United States
Garib N. Murshudov United Kingdom
Martyn Winn United Kingdom
Jeffrey J. Headd United States
Randy J. Read relative to Paul D. Adams United States Paul D. Adams's profile →
Citations per field
00.5×1.5×
Paul D. Adams · 1×
Citations per year

Countries citing papers authored by Randy J. Read

Since Specialization
Citations

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

Fields of papers citing papers by Randy J. Read

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Randy J. Read. 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 Randy J. Read. The network helps show where Randy J. Read may publish in the future.

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 202315
2 202334
3 20232
4 20236
5 202119
6 202028
7 2020197
8 201938
9
Real-space refinement in PHENIX for cryo-EM and crystallographybreakdown →
20182004
10 201833
11 2014201
12 2012112
13 200973
14 200733
15 20076
16 2007242
17 199777
18 1992145
19 199210
20 19918

About Randy J. Read

Randy J. Read is a scholar working on Structural Biology, Materials Chemistry, Endocrinology, Molecular Biology and Spectroscopy, having authored 197 papers that have together received 86.9k indexed citations. Recurring topics across this work include Enzyme Structure and Function (93 papers), Protein Structure and Dynamics (71 papers), RNA and protein synthesis mechanisms (17 papers), Computational Drug Discovery Methods (14 papers), Machine Learning in Materials Science (13 papers), Advanced Electron Microscopy Techniques and Applications (13 papers), X-ray Diffraction in Crystallography (12 papers) and Toxin Mechanisms and Immunotoxins (10 papers). The work is most often cited by research in Molecular Biology (62.2k citations), Structural Biology (1.1k citations), Endocrinology (2.7k citations), Biotechnology (4.3k citations) and Cell Biology (7.9k citations). Randy J. Read has collaborated with scholars based in United Kingdom, United States and Canada. Frequent co-authors include Paul D. Adams, Ralf W. Grosse‐Kunstleve, Airlie J. McCoy, Laurent C. Storoni, Martyn Winn, Thomas C. Terwilliger, Neesh Pannu, Nigel W. Moriarty, Li‐Wei Hung and Pavel V. Afonine. Their work appears in journals such as Acta Crystallographica Section D Structural Biology, Journal of Molecular Biology, Proteins Structure Function and Bioinformatics, Proceedings of the National Academy of Sciences and Structure.

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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