Mat Soukup

1.3k total citations
9 papers, 225 citations indexed

About

Mat Soukup is a scholar working on Molecular Biology, Statistics and Probability and Endocrinology, Diabetes and Metabolism. According to data from OpenAlex, Mat Soukup has authored 9 papers receiving a total of 225 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Molecular Biology, 4 papers in Statistics and Probability and 2 papers in Endocrinology, Diabetes and Metabolism. Recurrent topics in Mat Soukup's work include Statistical Methods in Clinical Trials (4 papers), Health Systems, Economic Evaluations, Quality of Life (2 papers) and Molecular Biology Techniques and Applications (2 papers). Mat Soukup is often cited by papers focused on Statistical Methods in Clinical Trials (4 papers), Health Systems, Economic Evaluations, Quality of Life (2 papers) and Molecular Biology Techniques and Applications (2 papers). Mat Soukup collaborates with scholars based in United States and Switzerland. Mat Soukup's co-authors include Cynthia Kornegay, Kendall A. Marcus, Peter Miele, Xiao Ding, Charles K. Cooper, Matthew A. Psioda, Joseph G. Ibrahim, HyungJun Cho, Jae K. Lee and Taxiarchis Botsis and has published in prestigious journals such as Diabetes Care, Statistics in Medicine and JAIDS Journal of Acquired Immune Deficiency Syndromes.

In The Last Decade

Mat Soukup

9 papers receiving 224 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Mat Soukup United States	6	104	99	68	34	33	9	225
Dimitrios Pilalas Greece	10	18 0.2×	84 0.8×	50 0.7×	5 0.1×	66 2.0×	33	238
Casimir Ledoux Sofeu France	8	18 0.2×	50 0.5×	40 0.6×	32 0.9×	21 0.6×	15	186
Gill Pearce United States	3	77 0.7×	182 1.8×	126 1.9×	6 0.2×	58 1.8×	3	375
Rachel Ceccarelli United States	5	30 0.3×	70 0.7×	23 0.3×	4 0.1×	40 1.2×	8	222
Thomas Kelleher United States	7	193 1.9×	302 3.1×	245 3.6×	8 0.2×	30 0.9×	11	380
Sumanth Karamchand South Africa	6	34 0.3×	49 0.5×	15 0.2×	7 0.2×	21 0.6×	12	129
Giovanni Carpani Italy	9	15 0.1×	29 0.3×	40 0.6×	11 0.3×	27 0.8×	21	203
J Lange Netherlands	9	56 0.5×	193 1.9×	147 2.2×	2 0.1×	55 1.7×	17	248
Marit G. A. van Vonderen Netherlands	8	200 1.9×	100 1.0×	114 1.7×	2 0.1×	52 1.6×	12	322
Rosaria Viglietti Italy	9	50 0.5×	105 1.1×	37 0.5×		44 1.3×	19	223

Countries citing papers authored by Mat Soukup

Since Specialization

Citations

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

Fields of papers citing papers by Mat Soukup

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mat Soukup

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

All Works

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9 of 9 papers shown

1.

Soukup, Mat, et al.. (2022). A structured framework for adaptively incorporating external evidence in sequentially monitored clinical trials. Journal of Biopharmaceutical Statistics. 32(3). 474–495. 2 indexed citations

2.

Bradley, Marie C., Yoganand Chillarige, Hana Lee, et al.. (2020). Similar Breast Cancer Risk in Women Older Than 65 Years Initiating Glargine, Detemir, and NPH Insulins. Diabetes Care. 43(4). 785–792. 3 indexed citations

3.

Psioda, Matthew A., Mat Soukup, & Joseph G. Ibrahim. (2018). A practical Bayesian adaptive design incorporating data from historical controls. Statistics in Medicine. 37(27). 4054–4070. 24 indexed citations

4.

Izem, Rima, et al.. (2015). The role of quantitative safety evaluation in regulatory decision making of drugs. Journal of Biopharmaceutical Statistics. 26(1). 17–29. 4 indexed citations

5.

Duke, Susan P., et al.. (2015). Seeing is believing: good graphic design principles for medical research. Statistics in Medicine. 34(22). 3040–3059. 29 indexed citations

6.

Ding, Xiao, Charles K. Cooper, Peter Miele, et al.. (2012). No Association of Abacavir Use With Myocardial Infarction. JAIDS Journal of Acquired Immune Deficiency Syndromes. 61(4). 441–447. 127 indexed citations

7.

Alosh, Mohamed, et al.. (2009). Clinical trials and statistical analyses: what should dermatologists look for in a report?. Dermatologic Therapy. 22(3). 199–203. 5 indexed citations

8.

Soukup, Mat, et al.. (2005). Robust classification modeling on microarray data using misclassification penalized posterior. Computer applications in the biosciences. 21(Suppl 1). i423–i430. 20 indexed citations

9.

Soukup, Mat & Jae K. Lee. (2004). DEVELOPING OPTIMAL PREDICTION MODELS FOR CANCER CLASSIFICATION USING GENE EXPRESSION DATA. Journal of Bioinformatics and Computational Biology. 1(4). 681–694. 11 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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