Joe Swintek

605 total citations
17 papers, 492 citations indexed

About

Joe Swintek is a scholar working on Health, Toxicology and Mutagenesis, Pollution and Nature and Landscape Conservation. According to data from OpenAlex, Joe Swintek has authored 17 papers receiving a total of 492 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Health, Toxicology and Mutagenesis, 9 papers in Pollution and 4 papers in Nature and Landscape Conservation. Recurrent topics in Joe Swintek's work include Pharmaceutical and Antibiotic Environmental Impacts (9 papers), Environmental Toxicology and Ecotoxicology (8 papers) and Effects and risks of endocrine disrupting chemicals (4 papers). Joe Swintek is often cited by papers focused on Pharmaceutical and Antibiotic Environmental Impacts (9 papers), Environmental Toxicology and Ecotoxicology (8 papers) and Effects and risks of endocrine disrupting chemicals (4 papers). Joe Swintek collaborates with scholars based in United States, Ghana and Japan. Joe Swintek's co-authors include Daniel L. Villeneuve, Gerald T. Ankley, Brett R. Blackwell, Keith A. Houck, Sergei S. Makarov, Paul M. Bradley, Alexander V. Medvedev, Kevin Flynn, Timothy A. Springer and John W. Green and has published in prestigious journals such as Environmental Science & Technology, Toxicological Sciences and Environmental Toxicology and Chemistry.

In The Last Decade

Joe Swintek

17 papers receiving 485 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Joe Swintek United States 10 333 227 74 52 43 17 492
Kellie A. Fay United States 12 303 0.9× 207 0.9× 32 0.4× 36 0.7× 22 0.5× 17 419
Silvia Maggioni Italy 8 364 1.1× 317 1.4× 102 1.4× 73 1.4× 34 0.8× 11 592
Cléo Tebby France 15 298 0.9× 192 0.8× 21 0.3× 47 0.9× 24 0.6× 35 532
Travis Saari United States 8 153 0.5× 103 0.5× 71 1.0× 65 1.3× 20 0.5× 10 320
Chad Blanksma United States 10 267 0.8× 250 1.1× 134 1.8× 45 0.9× 53 1.2× 12 501
Jonathan T. Haselman United States 13 279 0.8× 79 0.3× 56 0.8× 97 1.9× 16 0.4× 20 526
Maurice Zeeman United States 9 412 1.2× 187 0.8× 49 0.7× 52 1.0× 33 0.8× 18 729
Barbara R. Sheedy United States 10 247 0.7× 139 0.6× 49 0.7× 25 0.5× 13 0.3× 22 356
Evelyn Stinckens Belgium 10 266 0.8× 83 0.4× 93 1.3× 58 1.1× 16 0.4× 10 448
Marilynn D. Hoglund United States 10 325 1.0× 205 0.9× 74 1.0× 53 1.0× 30 0.7× 17 517

Countries citing papers authored by Joe Swintek

Since Specialization
Citations

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

Fields of papers citing papers by Joe Swintek

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Joe Swintek

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

All Works

17 of 17 papers shown
1.
Pollesch, Nathan, et al.. (2021). Developing integral projection models for ecotoxicology. Ecological Modelling. 464. 109813–109813. 5 indexed citations
2.
Nichols, John W., Alex D. Hoffman, Joe Swintek, Steven T. J. Droge, & Patrick N. Fitzsimmons. (2020). Addition of Phenylmethylsulfonyl Fluoride Increases the Working Lifetime of the Trout Liver S9 Substrate Depletion Assay, Resulting in Improved Detection of Low Intrinsic Clearance Rates. Environmental Toxicology and Chemistry. 40(1). 148–161. 8 indexed citations
3.
Ankley, Gerald T., Jason P. Berninger‌, Brett R. Blackwell, et al.. (2020). Pathway-Based Approaches for Assessing Biological Hazards of Complex Mixtures of Contaminants: A Case Study in the Maumee River. Environmental Toxicology and Chemistry. 40(4). 1098–1122. 17 indexed citations
4.
5.
Swintek, Joe, Matthew A. Etterson, Kevin Flynn, & Rodney D. Johnson. (2019). Optimized temporal sampling designs of the Weibull growth curve with extensions to the von Bertalanffy model. Environmetrics. 30(6). 7 indexed citations
6.
Blackwell, Brett R., Gerald T. Ankley, Paul M. Bradley, et al.. (2018). Potential Toxicity of Complex Mixtures in Surface Waters from a Nationwide Survey of United States Streams: Identifying in Vitro Bioactivities and Causative Chemicals. Environmental Science & Technology. 53(2). 973–983. 89 indexed citations
7.
LaLone, Carlie A., Daniel L. Villeneuve, Jon A. Doering, et al.. (2018). Evidence for Cross Species Extrapolation of Mammalian-Based High-Throughput Screening Assay Results. Environmental Science & Technology. 52(23). 13960–13971. 56 indexed citations
8.
Cavallin, Jenna E., Gerald T. Ankley, Eric C. Randolph, et al.. (2018). Gene transcription ontogeny of hypothalamic-pituitary-thyroid axis development in early-life stage fathead minnow and zebrafish. General and Comparative Endocrinology. 266. 87–100. 44 indexed citations
9.
10.
Fay, Kellie A., Daniel L. Villeneuve, Joe Swintek, et al.. (2018). Differentiating Pathway-Specific From Nonspecific Effects in High-Throughput Toxicity Data: A Foundation for Prioritizing Adverse Outcome Pathway Development. Toxicological Sciences. 163(2). 500–515. 44 indexed citations
11.
Nichols, John W., Kellie A. Fay, Mary Jo Bernhard, et al.. (2018). Reliability of In Vitro Methods Used to Measure Intrinsic Clearance of Hydrophobic Organic Chemicals by Rainbow Trout: Results of an International Ring Trial. Toxicological Sciences. 164(2). 563–575. 44 indexed citations
12.
Blackwell, Brett R., Gerald T. Ankley, Steven R. Corsi, et al.. (2017). An “EAR” on Environmental Surveillance and Monitoring: A Case Study on the Use of Exposure–Activity Ratios (EARs) to Prioritize Sites, Chemicals, and Bioactivities of Concern in Great Lakes Waters. Environmental Science & Technology. 51(15). 8713–8724. 90 indexed citations
13.
Flynn, Kevin, Dean E. Hammermeister, Leslie W. Touart, et al.. (2017). Summary of the development the US Environmental Protection Agency's Medaka Extended One Generation Reproduction Test (MEOGRT) using data from 9 multigenerational medaka tests. Environmental Toxicology and Chemistry. 36(12). 3387–3403. 20 indexed citations
14.
Flynn, Kevin, Joe Swintek, & Rodney D. Johnson. (2016). The influence of control group reproduction on the statistical power of the Environmental Protection Agency's Medaka Extended One Generation Reproduction Test (MEOGRT). Ecotoxicology and Environmental Safety. 136. 8–13. 3 indexed citations
15.
Green, John W., et al.. (2014). Statistical analysis of histopathological endpoints. Environmental Toxicology and Chemistry. 33(5). 1108–1116. 38 indexed citations
16.
Flynn, Kevin, Joe Swintek, & Rodney D. Johnson. (2013). Use of gene expression data to determine effects on gonad phenotype in japanese medaka after exposure to trenbolone or estradiol. Environmental Toxicology and Chemistry. 32(6). 1344–1353. 7 indexed citations
17.
Axler, Richard P, et al.. (2009). Minnesota lake water quality on-line database and visualization tools for exploratory trend analyses. University of Minnesota Digital Conservancy (University of Minnesota). 2 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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2026