Stephen M. Krone

3.5k total citations · 1 hit paper
45 papers, 2.3k citations indexed

About

Stephen M. Krone is a scholar working on Genetics, Mathematical Physics and Sociology and Political Science. According to data from OpenAlex, Stephen M. Krone has authored 45 papers receiving a total of 2.3k indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Genetics, 15 papers in Mathematical Physics and 11 papers in Sociology and Political Science. Recurrent topics in Stephen M. Krone's work include Evolution and Genetic Dynamics (18 papers), Stochastic processes and statistical mechanics (15 papers) and Evolutionary Game Theory and Cooperation (11 papers). Stephen M. Krone is often cited by papers focused on Evolution and Genetic Dynamics (18 papers), Stochastic processes and statistical mechanics (15 papers) and Evolutionary Game Theory and Cooperation (11 papers). Stephen M. Krone collaborates with scholars based in United States, Sweden and Canada. Stephen M. Krone's co-authors include Claudia Neuhauser, Edward O. Garton, Jon S. Horne, Jesse S. Lewis, Eva M. Top, Ingemar Kaj, Martin Lascoux, Linda Rogers, Jarosław E. Król and Magnus Nordborg and has published in prestigious journals such as PLoS ONE, Ecology and Applied and Environmental Microbiology.

In The Last Decade

Stephen M. Krone

45 papers receiving 2.2k citations

Hit Papers

ANALYZING ANIMAL MOVEMENTS USING BROWNIAN BRIDGES 2007 2026 2013 2019 2007 200 400 600

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Stephen M. Krone United States 21 807 802 476 260 224 45 2.3k
A. Jamie Wood United Kingdom 30 320 0.4× 470 0.6× 554 1.2× 264 1.0× 110 0.5× 83 2.5k
Frank M. Stewart United States 21 883 1.1× 1.4k 1.8× 727 1.5× 406 1.6× 320 1.4× 36 2.9k
Jonathan W. Pitchford United Kingdom 27 745 0.9× 422 0.5× 855 1.8× 73 0.3× 348 1.6× 60 2.8k
Benjamin Kerr United States 27 692 0.9× 1.9k 2.4× 744 1.6× 107 0.4× 497 2.2× 55 3.5k
Sharon Bewick United States 19 289 0.4× 240 0.3× 322 0.7× 132 0.5× 352 1.6× 62 1.4k
Mark M. Tanaka Australia 29 279 0.3× 817 1.0× 652 1.4× 90 0.3× 188 0.8× 94 3.2k
Catherine S. Jones United Kingdom 32 1.6k 2.0× 823 1.0× 858 1.8× 33 0.1× 168 0.8× 111 3.7k
Margaret A. Riley United States 11 427 0.5× 1.2k 1.5× 809 1.7× 67 0.3× 371 1.7× 13 2.3k
Edo Kussell United States 22 267 0.3× 1.3k 1.6× 1.9k 4.1× 128 0.5× 162 0.7× 43 2.8k
Tamás Czárán Hungary 23 326 0.4× 812 1.0× 687 1.4× 19 0.1× 248 1.1× 47 2.1k

Countries citing papers authored by Stephen M. Krone

Since Specialization
Citations

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

Fields of papers citing papers by Stephen M. Krone

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Stephen M. Krone

This figure shows the co-authorship network connecting the top 25 collaborators of Stephen M. Krone. A scholar is included among the top collaborators of Stephen M. Krone 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 Stephen M. Krone. Stephen M. Krone is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Bull, James J., et al.. (2022). Modeling the therapeutic potential of defective interfering particles in the presence of immunity. Virus Evolution. 8(2). veac047–veac047. 3 indexed citations
2.
Nuismer, Scott L., et al.. (2021). A white noise approach to evolutionary ecology. Journal of Theoretical Biology. 521. 110660–110660. 10 indexed citations
3.
Tyson, Rebecca C., et al.. (2020). The Timing and Nature of Behavioural Responses Affect the Course of an Epidemic. Bulletin of Mathematical Biology. 82(1). 14–14. 25 indexed citations
4.
Bull, James J., Christopher H. Remien, & Stephen M. Krone. (2019). Gene-drive-mediated extinction is thwarted by population structure and evolution of sib mating. Evolution Medicine and Public Health. 2019(1). 66–81. 37 indexed citations
5.
Baumgaertner, Bert, et al.. (2018). Spatial opinion dynamics and the effects of two types of mixing. Physical review. E. 98(2). 22310–22310. 11 indexed citations
6.
Krone, Stephen M., et al.. (2016). A Computational Model of the Rainbow Trout Hypothalamus-Pituitary-Ovary-Liver Axis. PLoS Computational Biology. 12(4). e1004874–e1004874. 18 indexed citations
7.
Baumgaertner, Bert, Rebecca C. Tyson, & Stephen M. Krone. (2016). Opinion strength influences the spatial dynamics of opinion formation. Journal of Mathematical Sociology. 40(4). 207–218. 18 indexed citations
8.
Roychoudhury, Pavitra, et al.. (2014). The Impact of Spatial Structure on Viral Genomic Diversity Generated during Adaptation to Thermal Stress. PLoS ONE. 9(2). e88702–e88702. 5 indexed citations
9.
Gaze, William H., Stephen M. Krone, D. G. Joakim Larsson, et al.. (2013). Influence of Humans on Evolution and Mobilization of Environmental Antibiotic Resistome. Emerging infectious diseases. 19(7). 119 indexed citations
10.
Król, Jarosław E., Andrzej Wójtowicz, Linda Rogers, et al.. (2013). Invasion of E. coli biofilms by antibiotic resistance plasmids. Plasmid. 70(1). 110–119. 68 indexed citations
11.
Brown, Celeste J., et al.. (2013). Adaptive regulatory substitutions affect multiple stages in the life cycle of the bacteriophage ϕX174. BMC Evolutionary Biology. 13(1). 66–66. 8 indexed citations
12.
Top, Eva M., et al.. (2011). On the meaning and estimation of plasmid transfer rates for surface-associated and well-mixed bacterial populations. Journal of Theoretical Biology. 294. 144–152. 50 indexed citations
13.
Król, Jarosław E., Linda Rogers, Stephen M. Krone, & Eva M. Top. (2010). Dual Reporter System for In Situ Detection of Plasmid Transfer under Aerobic and Anaerobic Conditions. Applied and Environmental Microbiology. 76(13). 4553–4556. 16 indexed citations
14.
Top, Eva M., et al.. (2009). Accounting for mating pair formation in plasmid population dynamics. Journal of Theoretical Biology. 262(4). 711–719. 40 indexed citations
15.
Wei, Wei, et al.. (2009). Space, Time, and Host Evolution Facilitate Coexistence of Competing Bacteriophages: Theory and Experiment. The American Naturalist. 173(4). E121–E138. 14 indexed citations
16.
Horne, Jon S., Edward O. Garton, Stephen M. Krone, & Jesse S. Lewis. (2007). ANALYZING ANIMAL MOVEMENTS USING BROWNIAN BRIDGES. Ecology. 88(9). 2354–2363. 682 indexed citations breakdown →
17.
Krone, Stephen M. & Yongtao Guan. (2005). Spatial self-organization in a cyclic resource–species model. Journal of Theoretical Biology. 241(1). 14–25. 6 indexed citations
18.
Wei, Wei & Stephen M. Krone. (2005). Spatial invasion by a mutant pathogen. Journal of Theoretical Biology. 236(3). 335–348. 25 indexed citations
19.
Neuhauser, Claudia & Stephen M. Krone. (1997). The Genealogy of Samples in Models With Selection. Genetics. 145(2). 519–534. 201 indexed citations
20.
Ethier, S. N. & Stephen M. Krone. (1995). Comparing Fleming-Viot and Dawson-Watanabe processes. Stochastic Processes and their Applications. 60(2). 171–190. 10 indexed citations

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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