William A. McLaughlin

754 citations
22 papers · 651 · h-index 10

Impact in

Papers in

    • Protein Structure and Dynamics 9
    • RNA and protein synthesis mechanisms 8
    • Bioinformatics and Genomic Networks 6
    • Machine Learning in Bioinformatics 4
    • Receptor Mechanisms and Signaling 3
    • Genetics, Bioinformatics, and Biomedical Research 2
    • Enzyme Structure and Function 6

William A. McLaughlin

22 papers receiving 644 citations

Peers

William A. McLaughlin
Comparison fields: 5 of 88
  • Computational Theory and Mathematics 145
  • Virology 39
  • Molecular Biology 522
  • Infectious Diseases 77
  • Radiology, Nuclear Medicine and Imaging 59
Replace Élodie Laine with:
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Kristin L. Meagher United States
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Darren R. March Australia
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Wei Zu Chen China
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Citations per field
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Citations per year

Countries citing papers authored by William A. McLaughlin

Since Specialization
Citations

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

Fields of papers citing papers by William A. McLaughlin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by William A. McLaughlin. 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 William A. McLaughlin. The network helps show where William A. McLaughlin may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 22 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2006144
2 2007110
3 2008100
4 200567
5 200866
6 201159
7 201725
8 201917
9 200316
10 200613
11 19977
12 20105
13 20124
14 20114
15 20073
16 20133
17 20052
18 20222
19 20231
20 20201

About William A. McLaughlin

William A. McLaughlin is a scholar working on Molecular Biology, Materials Chemistry, Computational Theory and Mathematics, Cell Biology and Genetics, having authored 22 papers that have together received 651 indexed citations. Recurring topics across this work include Protein Structure and Dynamics (9 papers), RNA and protein synthesis mechanisms (8 papers), Bioinformatics and Genomic Networks (6 papers), Enzyme Structure and Function (6 papers), Machine Learning in Bioinformatics (4 papers), Receptor Mechanisms and Signaling (3 papers), Genetics, Bioinformatics, and Biomedical Research (2 papers) and Computational Drug Discovery Methods (2 papers). The work is most often cited by research in Computational Theory and Mathematics (145 citations), Virology (39 citations), Molecular Biology (522 citations), Infectious Diseases (77 citations) and Radiology, Nuclear Medicine and Imaging (59 citations). William A. McLaughlin has collaborated with scholars based in United States, Switzerland and China. Frequent co-authors include Tingjun Hou, Wei Wang, Wei Wang, Ken Chen, Benzhuo Lu, David A. Case, Wei Zhang, Yang Xu, Riccardo Baron and Chia‐en A. Chang. Their work appears in journals such as Journal of Structural and Functional Genomics, Journal of Molecular Biology, Scientific Reports, Journal of Proteome Research and Bioinformatics.

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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