William A. McLaughlin
Impact in
-
- Computational Drug Discovery Methods
- Virology top 10%
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
- Chemical Synthesis and Analysis 2
- Virology 1
- Co-authors
- Tingjun HouWei WangKen ChenBenzhuo LuWei ZhangDavid A. CaseYang XuJ. Andrew McCammon
- Journals
- Journal of Structural and Functional Genomics (5 papers)Journal of Molecular Biology (2 papers)Scientific Reports (1 paper)Journal of Proteome Research (1 paper)Molecular & Cellular Proteomics (1 paper)
- Partner nations
- United StatesSwitzerlandChina
In The Last Decade
William A. McLaughlin
22 papers receiving 644 citations
Peers
Comparison fields: 5 of 88
- Computational Theory and Mathematics 145
- Virology 39
- Molecular Biology 522
- Infectious Diseases 77
- Radiology, Nuclear Medicine and Imaging 59
Countries citing papers authored by William A. McLaughlin
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
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.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2023 | 1 | |
| 2 | 2022 | 2 | |
| 3 | 2020 | 1 | |
| 4 | 2019 | 17 | |
| 5 | 2017 | 25 | |
| 6 | 2013 | 1 | |
| 7 | 2013 | 3 | |
| 8 | 2012 | 4 | |
| 9 | 2011 | 59 | |
| 10 | 2010 | 5 | |
| 11 | 2008 | 66 | |
| 12 | 2008 | 100 | |
| 13 | 2007 | 3 | |
| 14 | 2007 | 110 | |
| 15 | 2006 | 13 | |
| 16 | 2006 | 144 | |
| 17 | 2005 | 2 | |
| 18 | 2004 | 1 | |
| 19 | 2003 | 16 | |
| 20 | 1997 | 7 |
About William A. McLaughlin
William A. McLaughlin is a scholar working on Molecular Biology, Virology, Materials Chemistry, Computational Theory and Mathematics and Cell Biology, 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), Chemical Synthesis and Analysis (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, Ken Chen, Wei Wang, Benzhuo Lu, Wei Zhang, David A. Case, Yang Xu, J. Andrew McCammon 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 Molecular & Cellular Proteomics.
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.