Much of the work carried out by DTT is in support of the National Toxicology Program (NTP), an interagency partnership of the Food and Drug Administration, National Institute for Occupational Safety and Health, and NIEHS.
Toxicoinformatics Group
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Fred Parham, Ph.D.
Mathematical Statistician
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Tel 984-287-3169
[email protected]
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P.O. Box 12233
Mail Drop K2-17
Durham, NC 27709
Fred Parham, Ph.D., is a mathematical statistician in the Toxicoinformatics Group within the Predictive Toxicology Branch of the Division of Translational Toxicology. He came to the Branch in the summer of 2010 after spending several years working in the Environmental Systems Biology group of the NIEHS Division of Intramural Research. He is currently working on various projects involving the analysis and interpretation of high throughput screening data. He received his B. S. in mathematics from Duke University in 1984 and his Ph. D. from Princeton University in 1989.
ER AR1 18-M167, Mixture of AR- and ER-active chemicals
Recent Publications
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Parham F, Eccles K, Rider C, Sakamuru S, Xia M, Huang R, Tice R, Dinse G, Devito M. Lessons learned from evaluating defined chemical mixtures in a high throughput estrogen receptor assay system.
Toxicological sciences : an official journal of the Society of Toxicology.
2025 Feb 20 [Epub ahead of print].
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AbstractParham F, Eccles K, Rider C, Sakamuru S, Xia M, Huang R, Tice R, Dinse G, Devito M. Lessons learned from evaluating defined chemical mixtures in a high throughput estrogen receptor assay system. Toxicological sciences : an official journal of the Society of Toxicology. 2025 Feb 20
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Zilber D, Messier K, House J, Parham F, Auerbach S, Wheeler M. Bayesian gene set benchmark dose estimation for "omic" responses.
Bioinformatics (Oxford, England).
2024 Dec 26;41(1):.
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AbstractZilber D, Messier K, House J, Parham F, Auerbach S, Wheeler M. Bayesian gene set benchmark dose estimation for "omic" responses. Bioinformatics (Oxford, England). 2024 Dec 26
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Mansouri K, Taylor K, Auerbach S, Ferguson S, Frawley R, Hsieh J, Jahnke G, Kleinstreuer N, Mehta S, Moreira-Filho J, Parham F, Rider C, Rooney A, Wang A, Sutherland V. Unlocking the Potential of Clustering and Classification Approaches: Navigating Supervised and Unsupervised Chemical Similarity.
Environmental health perspectives.
2024 Aug;132(8):85002.
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AbstractMansouri K, Taylor K, Auerbach S, Ferguson S, Frawley R, Hsieh J, Jahnke G, Kleinstreuer N, Mehta S, Moreira-Filho J, Parham F, Rider C, Rooney A, Wang A, Sutherland V. Unlocking the Potential of Clustering and Classification Approaches: Navigating Supervised and Unsupervised Chemical Similarity. Environmental health perspectives. 2024 Aug
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Eccles K, Karmaus A, Kleinstreuer N, Parham F, Rider C, Wambaugh J, Messier K. A geospatial modeling approach to quantifying the risk of exposure to environmental chemical mixtures via a common molecular target.
The Science of the total environment.
2023 Jan 10;855:158905.
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AbstractEccles K, Karmaus A, Kleinstreuer N, Parham F, Rider C, Wambaugh J, Messier K. A geospatial modeling approach to quantifying the risk of exposure to environmental chemical mixtures via a common molecular target. The Science of the total environment. 2023 Jan 10
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Hsieh J, Behl M, Parham F, Ryan K. Exploring the Influence of Experimental Design on Toxicity Outcomes in Zebrafish Embryo Tests.
Toxicological sciences : an official journal of the Society of Toxicology.
2022 Jul 28;188(2):198-207.
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AbstractHsieh J, Behl M, Parham F, Ryan K. Exploring the Influence of Experimental Design on Toxicity Outcomes in Zebrafish Embryo Tests. Toxicological sciences : an official journal of the Society of Toxicology. 2022 Jul 28
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More Recent Publications from PubMed
