Tim Guilliams
Impact in
- Computational Theory and Mathematics top 0.5%
- Computational Drug Discovery Methods
- Neurology top 2%
- Parkinson's Disease Mechanisms and Treatments
Papers in
-
- Parkinson's Disease Mechanisms and Treatments 8
- Neurological disorders and treatments 2
-
- Cellular transport and secretion 5
- Co-authors
- David CavallaAndrew J. DoigShirley HopperSudeep PushpakomKatherine J. EscottChristine J. McNameePatrick A. EyersJoanna Latimer
- Journals
- Journal of Molecular Biology (2 papers)Brain Communications (1 paper)Orphanet Journal of Rare Diseases (1 paper)BMC Biology (1 paper)Journal of Biological Chemistry (1 paper)
- Partner nations
- United KingdomSpainItaly
In The Last Decade
Tim Guilliams
15 papers receiving 3.9k citations
Hit Papers
Peers
Comparison fields: 5 of 150
- Computational Theory and Mathematics 932
- Neurology 564
- Molecular Biology 2.0k
- Infectious Diseases 521
- Physiology 553
Countries citing papers authored by Tim Guilliams
This map shows the geographic impact of Tim Guilliams'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 Tim Guilliams with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tim Guilliams more than expected).
Fields of papers citing papers by Tim Guilliams
This network shows the impact of papers produced by Tim Guilliams. 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 Tim Guilliams. The network helps show where Tim Guilliams may publish in the future.
Co-authors
The 25 scholars most cited alongside Tim Guilliams, 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 | 2 | |
| 2 | 2019 | 19 | |
| 3 | Drug repurposing: progress, challenges and recommendations Hit paper breakdown → | 2018 | 2940 |
| 4 | 2018 | 25 | |
| 5 | 2018 | 25 | |
| 6 | 2018 | 13 | |
| 7 | 2018 | 21 | |
| 8 | 2017 | 59 | |
| 9 | 2016 | 21 | |
| 10 | Structural characterization of toxic oligomers that are kinetically trapped during α-synuclein fibril formation Hit paper breakdown → | 2015 | 368 |
| 11 | 2014 | 1 | |
| 12 | 2013 | 170 | |
| 13 | 2013 | 83 | |
| 14 | 2013 | 89 | |
| 15 | 2010 | 147 |
About Tim Guilliams
Tim Guilliams is a scholar working on Neurology, Cell Biology, Neurology, Physiology and Computational Theory and Mathematics, having authored 15 papers that have together received 4.0k indexed citations. Recurring topics across this work include Parkinson's Disease Mechanisms and Treatments (8 papers), Cellular transport and secretion (5 papers), Genetics and Neurodevelopmental Disorders (3 papers), Computational Drug Discovery Methods (3 papers), Glycosylation and Glycoproteins Research (2 papers), Alzheimer's disease research and treatments (2 papers), Neurological disorders and treatments (2 papers) and Genomics and Rare Diseases (1 paper). The work is most often cited by research in Computational Theory and Mathematics (932 citations), Neurology (564 citations), Molecular Biology (2.0k citations), Infectious Diseases (521 citations) and Physiology (553 citations). Tim Guilliams has collaborated with scholars based in United Kingdom, Spain and Italy. Frequent co-authors include David Cavalla, Andrew J. Doig, Shirley Hopper, Sudeep Pushpakom, Katherine J. Escott, Christine J. McNamee, Patrick A. Eyers, Joanna Latimer, Francesco Iorio and Andrew D. Wells. Their work appears in journals such as Journal of Molecular Biology, Brain Communications, Orphanet Journal of Rare Diseases, BMC Biology and Journal of Biological Chemistry.
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.