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Records 1 to 25 of 48

Harrill, J., L. Everett, D. Haggard, J. Bundy, C. Willis, I. Shah, K. Friedman, D. Basili, A. Middleton, AND R. Judson. Exploring the Effects of Experimental Parameters and Data Modeling Approaches on In Vitro Transcriptomic Point-of-Departure Estimates. TOXICOLOGY. Elsevier Science Ltd, New York, NY, 501:153694, (2024). https://doi.org/10.1016/j.tox.2023.153694
Tetko, I., G. Klambauer, D. Clevert, I. Shah, AND E. Benfenati. Artificial Intelligence Meets Toxicology. CHEMICAL RESEARCH IN TOXICOLOGY. American Chemical Society, Washington, DC, 35(8):1289-1290, (2022). https://doi.org/10.1021/acs.chemrestox.2c00196
Chambers, B. AND I. Shah. Evaluating adaptive stress response gene signatures using transcriptomics. Computational Toxicology. Elsevier B.V., Amsterdam, Netherlands, 20:100179, (2021). https://doi.org/10.1016/j.comtox.2021.100179
Foster, M., G. Patlewicz, I. Shah, D. Haggard, R. Judson, AND K. Friedman. Evaluating structure-based activity in a high-throughput assay for steroid biosynthesis. Computational Toxicology. Elsevier B.V., Amsterdam, Netherlands, 24:100245, (2022). https://doi.org/10.1016/j.comtox.2022.100245
Nyffeler, J., C. Willis, F. Harris, M. Foster, B. Chambers, M. Culbreth, R. Brockway, S. Davidson-Fritz, D. Dawson, I. Shah, K. Paul-Friedman, D. Chang, L. Everett, J. Wambaugh, G. Patlewicz, AND J. Harrill. Application of Cell Painting for chemical hazard evaluation in support of screening-level chemical assessments. TOXICOLOGY AND APPLIED PHARMACOLOGY. Academic Press Incorporated, Orlando, FL, 468:116513, (2023). https://doi.org/10.1016/j.taap.2023.116513
Shah, I., J. Bundy, B. Chambers, L. Everett, D. Haggard, J. Harrill, R. Judson, J. Nyffeler, AND G. Patlewicz. Navigating Transcriptomic Connectivity Mapping Workflows to Link Chemicals with Bioactivities. CHEMICAL RESEARCH IN TOXICOLOGY. American Chemical Society, Washington, DC, 35(11):1929-1949, (2022). https://doi.org/10.1021/acs.chemrestox.2c00245
Reardon, A., R. Farmahin, A. Williams, M. Meier, G. Addicks, C. Yauk, G. Matteo, E. Atlas, J. Harrill, L. Everett, I. Shah, R. Judson, S. Ramaiahgari, S. Ferguson, AND T. Barton-Maclaren. From vision toward best practices: Evaluating in vitro transcriptomic points of departure for application in risk assessment using a uniform workflow. Frontiers in Toxicology. Frontiers, Lausanne, Switzerland, 5:1194895, (2023). https://doi.org/10.3389/ftox.2023.1194895
Boyce, M., K. Favela, J. Bonzo, A. Chao, L. Lizarraga, L. Moody, E. Owens, G. Patlewicz, I. Shah, J. Sobus, R. Thomas, A. Williams, A. Yau, AND J. Wambaugh. Identifying xenobiotic metabolites with in silico prediction tools and LCMS suspect screening analysis. Frontiers in Toxicology. Frontiers, Lausanne, Switzerland, 5:1051483, (2023). https://doi.org/10.3389/ftox.2023.1051483
Tate, T., J. Wambaugh, G. Patlewicz, AND I. Shah. Repeat-dose toxicity prediction with Generalized Read-Across (GenRA) using targeted transcriptomic data: A proof-of-concept case study. Computational Toxicology. Elsevier B.V., Amsterdam, Netherlands, 19:100171, (2021). https://doi.org/10.1016/j.comtox.2021.100171
Patlewicz, G. AND I. Shah. Towards systematic read-across using Generalised Read-Across (GenRA). Computational Toxicology. Elsevier B.V., Amsterdam, Netherlands, 25:100258, (2023). https://doi.org/10.1016/j.comtox.2022.100258
Adams, M., H. Hilde, D. Chang, A. Richard, A. Williams, I. Shah, AND G. Patlewicz. Development of a CSRML version of the Analog identification Methodology (AIM) fragments and their evaluation within the Generalised Read-Across (GenRA) approach. Computational Toxicology. Elsevier B.V., Amsterdam, Netherlands, 25:100256, (2023). https://doi.org/10.1016/j.comtox.2022.100256
Bundy, J., R. Judson, A. Williams, C. Grulke, I. Shah, AND L. Everett. Predicting Molecular Initiating Events Using Chemical Target Annotations and Gene Expression. BioData Mining. BioMed Central Ltd, London, Uk, (15):7, (2022). https://doi.org/10.1186/s13040-022-00292-z
Shah, I., T. Tate, AND G. Patlewicz. Generalised Read-Across Prediction using genra-py. BIOINFORMATICS. Oxford University Press, Cary, NC, 37(19):3380-3381, (2021). https://doi.org/10.1093/bioinformatics/btab210
Lee, F., I. Shah, Y. Soong, J. Xing, I. Ng, F. Tasnim, AND H. Yu. Reproducibility and Robustness of High-Throughput S1500+ Transcriptomics on Primary Rat Hepatocytes for Chemical-Induced Hepatotoxicity Assessment. Current Research in Toxicology. Elsevier B.V., Amsterdam, Netherlands, 2:282-295, (2021). https://doi.org/10.1016/j.crtox.2021.07.003
Shah, I., T. Antonijevic, B. Chambers, J. Harrill, AND R. Thomas. Estimating Hepatotoxic Doses Using High-content Imaging in Primary Hepatocytes. TOXICOLOGICAL SCIENCES. Society of Toxicology, RESTON, VA, 183(2):285-301, (2021). https://doi.org/10.1093/toxsci/kfab091
Harrill, J., L. Everett, D. Haggard, T. Sheffield, J. Bundy, C. Willis, R. Thomas, I. Shah, AND R. Judson. High-Throughput Transcriptomics Platform for Screening Environmental Chemicals. TOXICOLOGICAL SCIENCES. Society of Toxicology, RESTON, VA, 181(1):68-89, (2021). https://doi.org/10.1093/toxsci/kfab009
Rivetti, C., T. Allen, J. Brown, E. Butler, P. Carmichael, J. Colbourne, M. Dent, F. Falciani, L. Gunnarsson, S. Gutsell, J. Harrill, G. Hodges, P. Jennings, R. Judson, A. Kienzler, L. Margiotta-Casaluci, I. Muller, S. Owen, C. Rendal, P. Russell, S. Scott, F. Sewell, I. Shah, I. Sorrel, M. Viant, C. Westmoreland, A. White, AND B. Campos. Vision of a near future: bridging the Human Health – Environment divide. Toward an integrated strategy to understand mechanisms across species for chemical safety assessment. TOXICOLOGY IN VITRO. Elsevier Science Ltd, New York, NY, 62:104692, (2020). https://doi.org/10.1016/j.tiv.2019.104692
Helman, G., G. Patlewicz, AND I. Shah. Quantitative Prediction of Repeat Dose Toxicity Values using GenRA. REGULATORY TOXICOLOGY AND PHARMACOLOGY. Elsevier Science Ltd, New York, NY, 109:104480, (2019). https://doi.org/10.1016/j.yrtph.2019.104480
Franzosa, J., J. Bonzo, J. Jack, Nancy C. Baker, P. Kothiya, R. Witek, P. Hurban, S. Siferd, S. Hester, I. Shah, S. Ferguson, K. Houck, AND J. Wambaugh. High-throughput toxicogenomic screening of chemicals in the environment using metabolically competent hepatic cell cultures. npj Systems Biology and Applications. Springer Nature, New York, NY, 7:Article 7, (2021). https://doi.org/10.1038/s41540-020-00166-2
Saili, K., T. Antonijevic, T. Zurlinden, I. Shah, C. Deisenroth, AND T. Knudsen. Molecular characterization of a toxicological tipping point during human stem cell differentiation. REPRODUCTIVE TOXICOLOGY. Elsevier Science Ltd, New York, NY, 91(January 2020):1-13, (2020). https://doi.org/10.1016/j.reprotox.2019.10.001
Helman, G., I. Shah, AND G. Patlewicz. Transitioning the Generalised Read-Across approach (GenRA) to quantitative predictions: A case study using acute oral toxicity data. Computational Toxicology. Elsevier B.V., Amsterdam, Netherlands, 12(November 2019):100097, (2019). https://doi.org/10.1016/j.comtox.2019.100097
Mansouri, K., N. Kleinstreuer, R. Judson, A. Williams, I. Shah, AND A. Richard. CoMPARA: Collaborative Modeling Project for Androgen Receptor Activity. ENVIRONMENTAL HEALTH PERSPECTIVES. National Institute of Environmental Health Sciences (NIEHS), Research Triangle Park, NC, 128(2):27002, (2020). https://doi.org/10.1289/EHP5580
Harrill, J., I. Shah, R. Setzer, D. Haggard, S. Auerbach, R. Judson, AND R. Thomas. Considerations for Strategic Use of High-Throughput Transcriptomics Chemical Screening Data in Regulatory Decisions. Current Opinion in Toxicology. Elsevier BV, AMSTERDAM, Netherlands, 15:64-75, (2019). https://doi.org/10.1016/j.cotox.2019.05.004
Helman, G., I. Shah, A. Williams, J. Edwards, J. Dunne, AND G. Patlewicz. Generalised Read-Across (GenRA): A workflow implemented into the EPA CompTox Chemicals Dashboard. ALTEX. Society ALTEX Edition, Kuesnacht, Switzerland, 36(1):1-5, (2019). https://doi.org/10.14573/altex.1811292