Paul S. Andrews
- Molecular Biology
- Artificial Intelligence top 10%
- Immunology
- Computational Theory and Mathematics top 5%
- Oncology
- Co-authors
- Jon TimmisMark ReadYue XiongMark ColesKieran AldenHenrique Veiga‐FernandesYizhou HeVipin Kumar
- Topics
- Gene Regulatory Network Analysis (10 papers)Evolution and Genetic Dynamics (7 papers)Ubiquitin and proteasome pathways (6 papers)
- Cited by
- Computational Theory and MathematicsManagement Science and Operations ResearchMolecular Biology
- Partner nations
- United KingdomUnited StatesAustralia
In The Last Decade
Paul S. Andrews
50 papers receiving 1.1k citations
Peers
Comparison fields: 5 of 150
- Molecular Biology 526
- Artificial Intelligence 164
- Immunology 146
- Computational Theory and Mathematics 140
- Oncology 132
Countries citing papers authored by Paul S. Andrews
This map shows the geographic impact of Paul S. Andrews'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 Paul S. Andrews with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Paul S. Andrews more than expected).
Fields of papers citing papers by Paul S. Andrews
This network shows the impact of papers produced by Paul S. Andrews. 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 Paul S. Andrews. The network helps show where Paul S. Andrews may publish in the future.
Co-authorship network of co-authors of Paul S. Andrews
This figure shows the co-authorship network connecting the top 25 collaborators of Paul S. Andrews. A scholar is included among the top collaborators of Paul S. Andrews based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Paul S. Andrews. Paul S. Andrews is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 4 | |
| 2 | 6 | |
| 3 | 1 | |
| 4 | CoSMoS 2015. Proceedings of the 2015 Workshop on Complex Systems Modelling and Simulation | 0 |
| 5 | 9 | |
| 6 | 37 | |
| 7 | 15 | |
| 8 | 10 | |
| 9 | 8 | |
| 10 | Proceedings of the 2012 Workshop on Complex Systems Modelling and Simulation | 7 |
| 11 | 10 | |
| 12 | 24 | |
| 13 | 39 | |
| 14 | 70 | |
| 15 | 5 | |
| 16 | 23 | |
| 17 | Investigating Patterns for the Process-Oriented Modelling and Simulation of Space in Complex Systems | 14 |
| 18 | 81 | |
| 19 | 25 | |
| 20 | How the Web was won : Microsoft from Windows to the Web : the inside story of how Bill Gates and his band of internet idealists transformed a software empire | 1 |
About Paul S. Andrews
Paul S. Andrews is a scholar working on Architecture, Modeling and Simulation and Management Science and Operations Research, having authored 52 papers that have together received 1.1k indexed citations. Recurring topics across this work include Gene Regulatory Network Analysis (10 papers), Evolution and Genetic Dynamics (7 papers) and Ubiquitin and proteasome pathways (6 papers). The work is most often cited by research in Computational Theory and Mathematics (140 citations), Management Science and Operations Research (99 citations) and Molecular Biology (526 citations). Paul S. Andrews has collaborated with scholars based in United Kingdom, United States and Australia. Frequent co-authors include Jon Timmis, Mark Read, Yue Xiong, Mark Coles, Kieran Alden, Henrique Veiga‐Fernandes, Yizhou He, Vipin Kumar, Emma Hart and Fiona Polack. Their work appears in journals such as Journal of Biological Chemistry, PLoS ONE and Nature Cell Biology.
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.