Daniel M. Cornforth

2.3k citations
16 papers · 1.5k indexed · h-index 13

Daniel M. Cornforth

15 papers receiving 1.4k citations

Peers

Daniel M. Cornforth
Comparison fields: 5 of 139
  • Endocrinology 180
  • Molecular Medicine 159
  • Modeling and Simulation 118
  • Genetics 442
  • Microbiology 72
Replace Timothy D. Minogue with:
Timothy D. Minogue United States
Enrico Lavezzo Italy
Pia Abel zur Wiesch United States
Lucy van Dorp United Kingdom
James W. Bullard United States
Michael B. Prentice United Kingdom
Xiaoping An China
Jana S. Huisman Switzerland
Henry H. Lee United States
François Blanquart France
Daniel M. Cornforth relative to Timothy D. Minogue United States Timothy D. Minogue's profile →
Citations per field
00.5×3.0×
Timothy D. Minogue · 1×
Citations per year

Countries citing papers authored by Daniel M. Cornforth

Since Specialization
Citations

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

Fields of papers citing papers by Daniel M. Cornforth

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel M. Cornforth. 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 Daniel M. Cornforth. The network helps show where Daniel M. Cornforth may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Daniel M. Cornforth, 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 Daniel M. Cornforth Line = papers co-authored together Daniel M. Cornforth links everyone, so they are left out of the graph.

All Works

16 of 16 papers shown
#Work
1 20250
2 20242
3 202334
4 20227
5 202094
6 2020105
7 201917
8 2018202
9 201612
10 201524
11 201480
12 2014129
13 2013342
14 201258
15 2012297
16 201160

About Daniel M. Cornforth

Daniel M. Cornforth is a scholar working on Modeling and Simulation, Genetics, Insect Science, Molecular Biology and Ecology, having authored 16 papers that have together received 1.5k indexed citations. Recurring topics across this work include Bacterial Genetics and Biotechnology (8 papers), Bacterial biofilms and quorum sensing (7 papers), Evolution and Genetic Dynamics (5 papers), Mathematical and Theoretical Epidemiology and Ecology Models (3 papers), COVID-19 epidemiological studies (2 papers), Bacteriophages and microbial interactions (2 papers), Microbial Community Ecology and Physiology (2 papers) and Biosensors and Analytical Detection (2 papers). The work is most often cited by research in Endocrinology (180 citations), Molecular Medicine (159 citations), Modeling and Simulation (118 citations), Genetics (442 citations) and Microbiology (72 citations). Daniel M. Cornforth has collaborated with scholars based in United States, United Kingdom and Canada. Frequent co-authors include Kevin R. Foster, Sam P. Brown, Nicole Mideo, Marvin Whiteley, Luke McNally, Roman Popat, Jonathan Dushoff, Joshua S. Weitz, Sang Woo Park and Jennifer M. Bomberger. Their work appears in journals such as Proceedings of the National Academy of Sciences, mBio, Emerging infectious diseases, The American Naturalist and PLoS Pathogens.

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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