Nicholas Geard
- Modeling and Simulation top 1%
- Infectious Diseases top 10%
- Epidemiology
- Molecular Biology
- Public Health, Environmental and Occupational Health
- Co-authors
- Jodie McVernonJanet WilesJames M. McCawPatricia T. CampbellSeth BullockAlan DorinKevin B. KorbEmma S. McBryde
- Topics
- COVID-19 epidemiological studies (23 papers)Evolutionary Game Theory and Cooperation (13 papers)Gene Regulatory Network Analysis (11 papers)
- Partner nations
- AustraliaUnited KingdomUnited States
In The Last Decade
Nicholas Geard
81 papers receiving 854 citations
Peers
Comparison fields: 5 of 138
- Modeling and Simulation 195
- Infectious Diseases 178
- Epidemiology 172
- Molecular Biology 153
- Public Health, Environmental and Occupational Health 121
Countries citing papers authored by Nicholas Geard
This map shows the geographic impact of Nicholas Geard'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 Nicholas Geard with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nicholas Geard more than expected).
Fields of papers citing papers by Nicholas Geard
This network shows the impact of papers produced by Nicholas Geard. 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 Nicholas Geard. The network helps show where Nicholas Geard may publish in the future.
Co-authorship network of co-authors of Nicholas Geard
This figure shows the co-authorship network connecting the top 25 collaborators of Nicholas Geard. A scholar is included among the top collaborators of Nicholas Geard 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 Nicholas Geard. Nicholas Geard is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 16 | |
| 5 | 5 | |
| 6 | 2 | |
| 7 | 58 | |
| 8 | 5 | |
| 9 | 52 | |
| 10 | 6 | |
| 11 | 25 | |
| 12 | 2 | |
| 13 | 6 | |
| 14 | 47 | |
| 15 | 28 | |
| 16 | Group formation and social evolution: a computational model | 6 |
| 17 | An individual based model examining the emergence of cooperative recognition in a social insect (Isoptera: Rhinotermitidae) | 2 |
| 18 | Perturbation Analysis: A Complex Systems Pattern | 4 |
| 19 | Evolving Gene Regulatory Networks for Cellular Morphogenesis | 3 |
| 20 | A gene regulatory network for cell differentiation in caenorhabditis elegans | 3 |
About Nicholas Geard
Nicholas Geard is a scholar working on Modeling and Simulation, Aging and Infectious Diseases, having authored 87 papers that have together received 884 indexed citations. Recurring topics across this work include COVID-19 epidemiological studies (23 papers), Evolutionary Game Theory and Cooperation (13 papers) and Gene Regulatory Network Analysis (11 papers). The work is most often cited by research in Modeling and Simulation (195 citations), Health (87 citations) and Infectious Diseases (178 citations). Nicholas Geard has collaborated with scholars based in Australia, United Kingdom and United States. Frequent co-authors include Jodie McVernon, Janet Wiles, James M. McCaw, Patricia T. Campbell, Seth Bullock, Alan Dorin, Kevin B. Korb, Emma S. McBryde, Kathryn Glass and Steven Y. C. Tong. Their work appears in journals such as Bioinformatics, PLoS ONE and Clinical Infectious Diseases.
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.