Drew Posny

14 papers receiving 328 citations

Peers

Drew Posny
Comparison fields: 5 of 45
  • Modeling and Simulation 156
  • Horticulture 26
  • Endocrinology 75
  • Public Health, Environmental and Occupational Health 183
  • Genetics 93
Replace Alison T. M. Lima with:
Alison T. M. Lima Brazil
Wilfredo R. Matias United States
Mats Gunnar Andersson Sweden
Diana J. Sherman United States
Céline Courtillon France
Abdoul Karim Sangaré Mali
Lala Ratsifasoamanana Madagascar
Voahangy Andrianaivoarimanana Madagascar
M.W. Stern New Zealand
Anna Germundsson Norway
Drew Posny relative to Alison T. M. Lima Brazil Alison T. M. Lima's profile →
Citations per field
00.5×10×15×22.3×
Alison T. M. Lima · 1×
Citations per year

Countries citing papers authored by Drew Posny

Since Specialization
Citations

This map shows the geographic impact of Drew Posny'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 Drew Posny with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Drew Posny more than expected).

Fields of papers citing papers by Drew Posny

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Drew Posny. 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 Drew Posny. The network helps show where Drew Posny may publish in the future.

Co-authors

The 25 scholars most cited alongside Drew Posny, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Drew Posny Line = papers co-authored together Drew Posny links everyone, so they are left out of the graph.

All Works

14 of 14 papers shown
#Work
1 202064
2 201561
3 201452
4 201440
5 201636
6 201925
7 202114
8 201914
9 20159
10 20158
11 20184
12 20204
13 20253
14 20203

About Drew Posny

Drew Posny is a scholar working on Public Health, Environmental and Occupational Health, Modeling and Simulation, Endocrinology, Plant Science and Genetics, having authored 14 papers that have together received 337 indexed citations. Recurring topics across this work include Mathematical and Theoretical Epidemiology and Ecology Models (7 papers), COVID-19 epidemiological studies (6 papers), Vibrio bacteria research studies (4 papers), Animal Disease Management and Epidemiology (2 papers), Insect symbiosis and bacterial influences (2 papers), Phytoplasmas and Hemiptera pathogens (2 papers), Evolution and Genetic Dynamics (2 papers) and Postharvest Quality and Shelf Life Management (1 paper). The work is most often cited by research in Modeling and Simulation (156 citations), Horticulture (26 citations), Endocrinology (75 citations), Public Health, Environmental and Occupational Health (183 citations) and Genetics (93 citations). Drew Posny has collaborated with scholars based in United States, Thailand and Zimbabwe. Frequent co-authors include Jin Wang, Jin Wang, Zindoga Mukandavire, Weiqi Luo, Xueying Wang, T. R. Gottwald, Frank J. Louws, Jinhe Bai, David G. Hall and Greg McCollum. Their work appears in journals such as Philosophical Transactions of the Royal Society B Biological Sciences, International Journal of Biomathematics, Mathematical Biosciences & Engineering, Discrete and Continuous Dynamical Systems - B and Journal of Biological Dynamics.

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.

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