John Fricks

796 total citations
26 papers, 503 citations indexed

About

John Fricks is a scholar working on Molecular Biology, Statistical and Nonlinear Physics and Cell Biology. According to data from OpenAlex, John Fricks has authored 26 papers receiving a total of 503 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Molecular Biology, 8 papers in Statistical and Nonlinear Physics and 8 papers in Cell Biology. Recurrent topics in John Fricks's work include Microtubule and mitosis dynamics (8 papers), stochastic dynamics and bifurcation (5 papers) and Stochastic processes and statistical mechanics (5 papers). John Fricks is often cited by papers focused on Microtubule and mitosis dynamics (8 papers), stochastic dynamics and bifurcation (5 papers) and Stochastic processes and statistical mechanics (5 papers). John Fricks collaborates with scholars based in United States, Cyprus and China. John Fricks's co-authors include Matthew J. Ferrari, Kathleen Wannemuehler, Peter M. Strebel, Abhijeet Anand, Emily Simons, Anthony Burton, William O. Hancock, Timothy C. Elston, M. Gregory Forest and Matthew L. Kutys and has published in prestigious journals such as The Lancet, Journal of Biological Chemistry and Biometrics.

In The Last Decade

John Fricks

26 papers receiving 478 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
John Fricks United States	12	213	154	99	96	84	26	503
Meng Shi China	18	109 0.5×	39 0.3×	22 0.2×	227 2.4×	103 1.2×	41	714
Alexander Ullrich Germany	11	110 0.5×	17 0.1×	67 0.7×	491 5.1×	39 0.5×	34	903
Marta Galanti United States	11	161 0.8×	57 0.4×	156 1.6×	50 0.5×	25 0.3×	22	524
Orlando Cenciarelli Italy	11	85 0.4×	19 0.1×	38 0.4×	118 1.2×	29 0.3×	34	461
D. Schenzle Germany	11	231 1.1×	42 0.3×	341 3.4×	33 0.3×	39 0.5×	26	726
Sarafa A. Iyaniwura Canada	11	64 0.3×	38 0.2×	181 1.8×	64 0.7×	9 0.1×	36	338
Elsa Hansen United States	12	81 0.4×	8 0.1×	222 2.2×	75 0.8×	34 0.4×	17	595
David J. Philp Australia	12	184 0.9×	35 0.2×	163 1.6×	52 0.5×	4 0.0×	21	587
Suani T. R. Pinho Brazil	16	41 0.2×	11 0.1×	406 4.1×	143 1.5×	9 0.1×	58	792
Gabriella Kiss United States	6	206 1.0×	7 0.0×	33 0.3×	166 1.7×	43 0.5×	10	799

Countries citing papers authored by John Fricks

Since Specialization

Citations

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

Fields of papers citing papers by John Fricks

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of John Fricks

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Fricks, John, et al.. (2024). A Semi-Markov Approach to Study a Group of Kinesin Motors. Bulletin of Mathematical Biology. 86(2). 15–15. 1 indexed citations

Davis, Trenton J., et al.. (2020). A Metabolomic Approach for Predicting Diurnal Changes in Cortisol. Metabolites. 10(5). 194–194. 7 indexed citations

Fricks, John, et al.. (2020). A kinetic dissection of the fast and superprocessive kinesin-3 KIF1A reveals a predominant one-head-bound state during its chemomechanical cycle. Journal of Biological Chemistry. 295(52). 17889–17903. 16 indexed citations

Mickolajczyk, Keith J., et al.. (2019). Insights into Kinesin-1 Stepping Dynamics from Brownian Dynamics Simulations and High-Resolution Tracking of Gold Nanoparticle-Labeled Motors. Biophysical Journal. 116(3). 410a–410a. 1 indexed citations

Mickolajczyk, Keith J., et al.. (2019). Insights into Kinesin-1 Stepping from Simulations and Tracking of Gold Nanoparticle-Labeled Motors. Biophysical Journal. 117(2). 331–345. 10 indexed citations

Davis, Trenton J., John Stufken, Christopher Plaisier, et al.. (2019). Monitoring changes in the healthy female metabolome across the menstrual cycle using GC × GC-TOFMS. Journal of Chromatography B. 1121. 48–57. 12 indexed citations

Eilertson, Kirsten, John Fricks, & Matthew J. Ferrari. (2019). Estimation and prediction for a mechanistic model of measles transmission using particle filtering and maximum likelihood estimation. Statistics in Medicine. 38(21). 4146–4158. 17 indexed citations

Fricks, John, et al.. (2016). Analysis of single particle diffusion with transient binding using particle filtering. Journal of Theoretical Biology. 401. 109–121. 15 indexed citations

Goldstein, Joshua, et al.. (2015). An Attraction–Repulsion Point Process Model for Respiratory Syncytial Virus Infections. Biometrics. 71(2). 376–385. 13 indexed citations

10.

Hughes, John, Shankar Shastry, William O. Hancock, & John Fricks. (2013). Estimating Velocity for Processive Motor Proteins with Random Detachment. Journal of Agricultural Biological and Environmental Statistics. 18(2). 204–217. 5 indexed citations

11.

Fricks, John, et al.. (2012). On the wavelet-based simulation of anomalous diffusion. Journal of Statistical Computation and Simulation. 84(4). 697–723. 2 indexed citations

12.

Simons, Emily, Matthew J. Ferrari, John Fricks, et al.. (2012). Assessment of the 2010 global measles mortality reduction goal: results from a model of surveillance data. The Lancet. 379(9832). 2173–2178. 224 indexed citations

13.

McKinley, Scott A., et al.. (2012). Statistical challenges in microrheology. Journal of Time Series Analysis. 33(5). 724–743. 11 indexed citations

14.

Hughes, John, William O. Hancock, & John Fricks. (2011). Kinesins with Extended Neck Linkers: A Chemomechanical Model for Variable-Length Stepping. Bulletin of Mathematical Biology. 74(5). 1066–1097. 11 indexed citations

15.

Hughes, John, William O. Hancock, & John Fricks. (2010). A matrix computational approach to kinesin neck linker extension. Journal of Theoretical Biology. 269(1). 181–194. 9 indexed citations

16.

Kutys, Matthew L., John Fricks, & William O. Hancock. (2010). Monte Carlo Analysis of Neck Linker Extension in Kinesin Molecular Motors. PLoS Computational Biology. 6(11). e1000980–e1000980. 28 indexed citations

17.

Hughes, John & John Fricks. (2010). A Mixture Model for Quantum Dot Images of Kinesin Motor Assays. Biometrics. 67(2). 588–595. 1 indexed citations

18.

Fricks, John, et al.. (2009). Time-Domain Methods for Diffusive Transport in Soft Matter. SIAM Journal on Applied Mathematics. 69(5). 1277–1308. 45 indexed citations

19.

Fricks, John, Hongyun Wang, & Timothy C. Elston. (2005). A numerical algorithm for investigating the role of the motor–cargo linkage in molecular motor-driven transport. Journal of Theoretical Biology. 239(1). 33–48. 12 indexed citations

20.

Fricks, John. (1999). A Stochastic Analog to the Richardson's Arms Race Model. TopSCHOLAR (Western Kentucky University). 1 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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