Lisa McWilliams
Impact in
- Molecular Medicine top 10%
- Antibiotic Resistance in Bacteria
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- Cell Image Analysis Techniques
Papers in
-
- Single-cell and spatial transcriptomics 1
- Ion channel regulation and function 1
- Protein Degradation and Inhibitors 1
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- Computational Drug Discovery Methods 3
- Co-authors
- Asha S. Nayar (1 shared paper)Sarah M. McLeod (1 shared paper)Thomas J. Dougherty (1 shared paper)Hajime Tokuda (1 shared paper)Lindsey Leach (1 shared paper)Alita A. Miller (1 shared paper)Dean G. Brown (1 shared paper)Keith Ferguson (1 shared paper)
- Journals
- SLAS DISCOVERY (2 papers)Assay and Drug Development Technologies (1 paper)Journal of Bacteriology (1 paper)Journal of Biological Chemistry (1 paper)Neuro-Oncology (1 paper)
- Partner nations
- United KingdomUnited StatesSweden
In The Last Decade
Lisa McWilliams
10 papers receiving 181 citations
Peers
Comparison fields: 5 of 69
- Molecular Medicine 45
- Biophysics 21
- Computational Theory and Mathematics 32
- Cellular and Molecular Neuroscience 29
- Molecular Biology 101
Countries citing papers authored by Lisa McWilliams
This map shows the geographic impact of Lisa McWilliams'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 Lisa McWilliams with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lisa McWilliams more than expected).
Fields of papers citing papers by Lisa McWilliams
This network shows the impact of papers produced by Lisa McWilliams. 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 Lisa McWilliams. The network helps show where Lisa McWilliams may publish in the future.
Co-authors
The 25 scholars most cited alongside Lisa McWilliams, 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 | 2015 | 90 | |
| 2 | 2016 | 32 | |
| 3 | 2017 | 30 | |
| 4 | 2017 | 14 | |
| 5 | 2022 | 7 | |
| 6 | 2021 | 5 | |
| 7 | 2016 | 4 | |
| 8 | 2015 | 3 | |
| 9 | 2022 | 2 | |
| 10 | 2018 | 1 |
About Lisa McWilliams
Lisa McWilliams is a scholar working on Molecular Biology, Computational Theory and Mathematics, Biophysics, Oncology and Small Animals, having authored 10 papers that have together received 188 indexed citations. Recurring topics across this work include Cell Image Analysis Techniques (3 papers), Computational Drug Discovery Methods (3 papers), Single-cell and spatial transcriptomics (1 paper), Ion channel regulation and function (1 paper), Protein Degradation and Inhibitors (1 paper), Antibiotic Resistance in Bacteria (1 paper), Bacterial Genetics and Biotechnology (1 paper) and Animal testing and alternatives (1 paper). The work is most often cited by research in Molecular Medicine (45 citations), Biophysics (21 citations), Computational Theory and Mathematics (32 citations), Cellular and Molecular Neuroscience (29 citations) and Molecular Biology (101 citations). Lisa McWilliams has collaborated with scholars based in United Kingdom, United States and Sweden. Frequent co-authors include Asha S. Nayar, Sarah M. McLeod, Thomas J. Dougherty, Hajime Tokuda, Lindsey Leach, Alita A. Miller, Dean G. Brown, Keith Ferguson, Shin‐ichiro Narita and David C. Murray. Their work appears in journals such as SLAS DISCOVERY, Assay and Drug Development Technologies, Journal of Bacteriology, Journal of Biological Chemistry and Neuro-Oncology.
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.