W. Clayton Thompson

604 total citations
23 papers, 441 citations indexed

About

W. Clayton Thompson is a scholar working on Molecular Biology, Immunology and Statistics and Probability. According to data from OpenAlex, W. Clayton Thompson has authored 23 papers receiving a total of 441 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Molecular Biology, 5 papers in Immunology and 5 papers in Statistics and Probability. Recurrent topics in W. Clayton Thompson's work include Single-cell and spatial transcriptomics (6 papers), Gene Regulatory Network Analysis (5 papers) and T-cell and B-cell Immunology (5 papers). W. Clayton Thompson is often cited by papers focused on Single-cell and spatial transcriptomics (6 papers), Gene Regulatory Network Analysis (5 papers) and T-cell and B-cell Immunology (5 papers). W. Clayton Thompson collaborates with scholars based in United States, Spain and France. W. Clayton Thompson's co-authors include H. T. Banks, Shuhua Hu, Andreas Meyerhans, Karyn L. Sutton, Cynthia J. Musante, Gennady Bocharov, H. T. Banks, Saswata Talukdar, Yingjiang Zhou and Jordi Argilaguet and has published in prestigious journals such as PLoS ONE, Biophysical Journal and International Journal of Obesity.

In The Last Decade

W. Clayton Thompson

22 papers receiving 416 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
W. Clayton Thompson United States	12	186	95	74	48	38	23	441
G. Bellu Italy	7	251 1.3×	76 0.8×	18 0.2×	50 1.0×	20 0.5×	9	643
Carolin Loos Germany	13	227 1.2×	35 0.4×	79 1.1×	39 0.8×	8 0.2×	20	537
Oliver J. Maclaren New Zealand	13	192 1.0×	93 1.0×	8 0.1×	34 0.7×	28 0.7×	37	499
Rahuman S. Malik‐Sheriff United Kingdom	11	409 2.2×	25 0.3×	31 0.4×	19 0.4×	26 0.7×	20	727
Christian Tönsing Germany	6	215 1.2×	46 0.5×	15 0.2×	18 0.4×	15 0.4×	8	394
Marcus Rosenblatt Germany	9	160 0.9×	32 0.3×	29 0.4×	13 0.3×	10 0.3×	13	339
L. D’Angiò Italy	7	146 0.8×	32 0.3×	14 0.2×	28 0.6×	13 0.3×	11	418
Marissa Renardy United States	9	54 0.3×	86 0.9×	20 0.3×	29 0.6×	10 0.3×	15	278
Sandra Waaijenborg Netherlands	11	178 1.0×	33 0.3×	57 0.8×	13 0.3×	27 0.7×	13	511
James E. Johndrow United States	10	302 1.6×	19 0.2×	323 4.4×	39 0.8×	54 1.4×	24	923

Countries citing papers authored by W. Clayton Thompson

Since Specialization

Citations

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

Fields of papers citing papers by W. Clayton Thompson

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by W. Clayton Thompson. 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 W. Clayton Thompson. The network helps show where W. Clayton Thompson may publish in the future.

Co-authorship network of co-authors of W. Clayton Thompson

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

All Works

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20 of 20 papers shown

Banks, H. T., et al.. (2019). Parameter estimation using aggregate data. Applied Mathematics Letters. 100. 105999–105999. 5 indexed citations

Banks, H. T. & W. Clayton Thompson. (2018). RANDOM DELAY DIFFERENTIAL EQUATIONS AND INVERSE PROBLEMS FOR AGGREGATE DATA PROBLEMS. NCSU Libraries Repository (North Carolina State University Libraries). 6(4). 4–16.

Selimkhanov, Jangir, W. Clayton Thompson, Juen Guo, Kevin D. Hall, & Cynthia J. Musante. (2017). A quantitative analysis of statistical power identifies obesity end points for improved in vivo preclinical study design. International Journal of Obesity. 41(8). 1306–1309. 5 indexed citations

Thompson, W. Clayton, et al.. (2017). An Integrated Model of Human Beta-Adrenergic Signaling and Ventricular Electrophysiology Reveals Contributors to Positive Inotropy. Biophysical Journal. 112(3). 403a–404a. 1 indexed citations

Selimkhanov, Jangir, W. Clayton Thompson, Terrell A. Patterson, et al.. (2016). Evaluation of a Mathematical Model of Rat Body Weight Regulation in Application to Caloric Restriction and Drug Treatment Studies. PLoS ONE. 11(5). e0155674–e0155674. 6 indexed citations

Thompson, W. Clayton, Yingjiang Zhou, Saswata Talukdar, & Cynthia J. Musante. (2016). PF-05231023, a long-acting FGF21 analogue, decreases body weight by reduction of food intake in non-human primates. Journal of Pharmacokinetics and Pharmacodynamics. 43(4). 411–425. 43 indexed citations

Banks, H. T. & W. Clayton Thompson. (2015). EXISTENCE AND CONSISTENCY OF A NONPARAMETRIC ESTIMATOR OF PROBABILITY MEASURES IN THE PROHOROV METRIC FRAMEWORK. International Journal of Pure and Apllied Mathematics. 103(4). 5 indexed citations

Thompson, W. Clayton, et al.. (2015). Correlation of parameter estimators for models admitting multiple parametrizations. NCSU Libraries Repository (North Carolina State University Libraries). 105(3). 497–522. 3 indexed citations

Banks, H. T., et al.. (2014). Analysis of variability in estimates of cell proliferation parameters for cyton-based models using CFSE-based flow cytometry data. Journal of Inverse and Ill-Posed Problems. 23(2). 135–171. 3 indexed citations

10.

Banks, H. T., et al.. (2013). Quantifying CFSE label decay in flow cytometry data. Applied Mathematics Letters. 26(5). 571–577. 12 indexed citations

11.

Banks, H. T., et al.. (2013). A novel statistical analysis and interpretation of flow cytometry data. Journal of Biological Dynamics. 7(1). 96–132. 12 indexed citations

12.

Banks, H. T., et al.. (2013). Experimental and biological variability in CFSE-based flow cytometry data. NCSU Libraries Repository (North Carolina State University Libraries). 2 indexed citations

13.

Banks, H. T., et al.. (2012). A division-dependent compartmental model for computing cell numbers in CFSE-based lymphocyte proliferation assays. Mathematical Biosciences & Engineering. 9(4). 699–736. 20 indexed citations

14.

Banks, H. T., et al.. (2012). A review of selected techniques in inverse problem nonparametric probability distribution estimation. Journal of Inverse and Ill-Posed Problems. 20(4). 429–460. 28 indexed citations

15.

Thompson, W. Clayton, et al.. (2012). Modeling CFSE label decay in flow cytometry data. NCSU Libraries Repository (North Carolina State University Libraries). 1 indexed citations

16.

Banks, H. T. & W. Clayton Thompson. (2012). Mathematical Models of Dividing Cell Populations: Application to CFSE Data. Mathematical Modelling of Natural Phenomena. 7(5). 24–52. 15 indexed citations

17.

Banks, H. T., Karyn L. Sutton, W. Clayton Thompson, et al.. (2011). A new model for the estimation of cell proliferation dynamics using CFSE data. Journal of Immunological Methods. 373(1-2). 143–160. 35 indexed citations

18.

Thompson, W. Clayton. (2011). Partial Differential Equation Modeling of Flow Cytometry Data from CFSE-based Proliferation Assays. NCSU Libraries Repository (North Carolina State University Libraries). 14 indexed citations

19.

Banks, H. T., et al.. (2010). Label structured cell proliferation models. Applied Mathematics Letters. 23(12). 1412–1415. 11 indexed citations

20.

Banks, H. T., Karyn L. Sutton, W. Clayton Thompson, et al.. (2010). Estimation of Cell Proliferation Dynamics Using CFSE Data. Bulletin of Mathematical Biology. 73(1). 116–150. 59 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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