Jack D. Dockery

890 citations
14 papers · 672 indexed · h-index 8

Impact in

Papers in

Jack D. Dockery

13 papers receiving 610 citations

Peers

Jack D. Dockery
Comparison fields: 5 of 104
  • Modeling and Simulation 151
  • Public Health, Environmental and Occupational Health 310
  • Genetics 283
  • Numerical Analysis 26
  • Endocrinology 20
Replace John E. Franke with:
John E. Franke United States
J. Dockery United States
Yu Jin United States
Lea F. Murphy United States
Samrat Chatterjee India
Yasuhisa Saito Japan
Jufang Chen China
Hristo V. Kojouharov United States
Dung Le United States
Jack D. Dockery relative to John E. Franke United States John E. Franke's profile →
Citations per field
00.5×5.2×
John E. Franke · 1×
Citations per year

Countries citing papers authored by Jack D. Dockery

Since Specialization
Citations

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

Fields of papers citing papers by Jack D. Dockery

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jack D. Dockery. 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 Jack D. Dockery. The network helps show where Jack D. Dockery may publish in the future.

Co-authorship network

The 19 scholars most cited alongside Jack D. Dockery, 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 Jack D. Dockery Line = papers co-authored together Jack D. Dockery links everyone, so they are left out of the graph.

All Works

14 of 14 papers shown
#Work
1 20220
2 20142
3 20115
4 20104
5 2010148
6 20099
7 2005104
8 19988
9 1998325
10 199732
11 19942
12 199319
13 19926
14 19928

About Jack D. Dockery

Jack D. Dockery is a scholar working on Modeling and Simulation, Endocrinology, Genetics, Public Health, Environmental and Occupational Health and Numerical Analysis, having authored 14 papers that have together received 672 indexed citations. Recurring topics across this work include Evolution and Genetic Dynamics (6 papers), Mathematical and Theoretical Epidemiology and Ecology Models (6 papers), Nonlinear Dynamics and Pattern Formation (3 papers), Bacterial biofilms and quorum sensing (2 papers), Mathematical Biology Tumor Growth (2 papers), Evolutionary Game Theory and Cooperation (2 papers), Viral gastroenteritis research and epidemiology (1 paper) and Legionella and Acanthamoeba research (1 paper). The work is most often cited by research in Modeling and Simulation (151 citations), Public Health, Environmental and Occupational Health (310 citations), Genetics (283 citations), Numerical Analysis (26 citations) and Endocrinology (20 citations). Jack D. Dockery has collaborated with scholars based in United States, Cyprus and United Kingdom. Frequent co-authors include Isaac Klapper, Mark Pernarowski, V. Hutson, Konstantin Mischaikow, Barbara Szomolay, Philip S. Stewart, John Lund, Paul Sturman, Warren L. Jones and Curtis R. Vogel. Their work appears in journals such as SIAM Journal on Applied Mathematics, Journal of Mathematical Biology, Biotechnology and Bioengineering, SIAM Journal on Mathematical Analysis and SIAM Review.

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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026