Imran Shah

Summary

Affiliation: U.S. Environmental Protection Agency
Country: USA

Publications

  1. ncbi Computational toxicology--a state of the science mini review
    Robert J Kavlock
    National Center for Computational Toxicology, Office of Research and Development, U S Environmental Protection Agency, Research Triangle Park, NC 27711, USA
    Toxicol Sci 103:14-27. 2008
  2. ncbi Virtual tissues in toxicology
    Imran Shah
    National Center for Computational Toxicology, Office of Research and Development, US Environmental Protection Agency, Research Triangle Park, North Carolina 27711, USA
    J Toxicol Environ Health B Crit Rev 13:314-28. 2010
  3. ncbi Using nuclear receptor activity to stratify hepatocarcinogens
    Imran Shah
    National Center for Computational Toxicology, Office of Research and Development, United States Environmental Protection Agency, Research Triangle Park, North Carolina, United States of America
    PLoS ONE 6:e14584. 2011
  4. ncbi In vitro screening of environmental chemicals for targeted testing prioritization: the ToxCast project
    Richard S Judson
    National Center for Computational Toxicology, Office of Research and Development, US Environmental Protection Agency, Research Triangle Park, North Carolina 27711, USA
    Environ Health Perspect 118:485-92. 2010
  5. ncbi Exposure science and the U.S. EPA National Center for Computational Toxicology
    Elaine A Cohen Hubal
    National Center for Computational Toxicology, US Environmental Protection Agency, Research Triangle Park, North Carolina 27711, USA
    J Expo Sci Environ Epidemiol 20:231-6. 2010
  6. ncbi Simulating microdosimetry in a virtual hepatic lobule
    John Wambaugh
    National Center for Computational Toxicology, Office of Research and Development, U S Environmental Protection Agency, Research Triangle Park, North Carolina, United States of America
    PLoS Comput Biol 6:e1000756. 2010
  7. ncbi In vitro perturbations of targets in cancer hallmark processes predict rodent chemical carcinogenesis
    Nicole C Kleinstreuer
    National Center for Computational Toxicology, Office of Research and Development, US Environmental Protection Agency, Research Triangle Park, North Carolina 27711, USA
    Toxicol Sci 131:40-55. 2013
  8. ncbi Using pathway modules as targets for assay development in xenobiotic screening
    Richard S Judson
    National Center for Computational Toxicology, Office of Research and Development, US Environmental Protection Agency, Research Triangle Park, NC 27711, USA
    Mol Biosyst 8:531-42. 2012
  9. ncbi Systems toxicology from genes to organs
    John Jack
    U S Environmental Protection Agency, Research Triangle Park, NC, USA
    Methods Mol Biol 930:375-97. 2013
  10. ncbi Simulating quantitative cellular responses using asynchronous threshold Boolean network ensembles
    John Jack
    National Center for Computational Toxicology, Office of Research and Development, US Environmental Protection Agency, Research Triangle Park, North Carolina, USA
    BMC Syst Biol 5:109. 2011

Collaborators

Detail Information

Publications11

  1. ncbi Computational toxicology--a state of the science mini review
    Robert J Kavlock
    National Center for Computational Toxicology, Office of Research and Development, U S Environmental Protection Agency, Research Triangle Park, NC 27711, USA
    Toxicol Sci 103:14-27. 2008
    ..The next few years should witness the early fruits of these efforts, but as the National Research Council indicates, the paradigm shift will take a long term investment and commitment to reach full potential...
  2. ncbi Virtual tissues in toxicology
    Imran Shah
    National Center for Computational Toxicology, Office of Research and Development, US Environmental Protection Agency, Research Triangle Park, North Carolina 27711, USA
    J Toxicol Environ Health B Crit Rev 13:314-28. 2010
    ..This investigation presents the motivation, implementation, and application of VT with examples from hepatotoxicity and carcinogenesis...
  3. ncbi Using nuclear receptor activity to stratify hepatocarcinogens
    Imran Shah
    National Center for Computational Toxicology, Office of Research and Development, United States Environmental Protection Agency, Research Triangle Park, North Carolina, United States of America
    PLoS ONE 6:e14584. 2011
    ..Here we report on a systematic analysis of new in vitro human NR activity data on 309 environmental chemicals in relationship to their liver cancer-related chronic outcomes in rodents...
  4. ncbi In vitro screening of environmental chemicals for targeted testing prioritization: the ToxCast project
    Richard S Judson
    National Center for Computational Toxicology, Office of Research and Development, US Environmental Protection Agency, Research Triangle Park, North Carolina 27711, USA
    Environ Health Perspect 118:485-92. 2010
    ..The U.S. Environmental Protection Agency's ToxCast program aims to address these concerns by screening and prioritizing chemicals for potential human toxicity using in vitro assays and in silico approaches...
  5. ncbi Exposure science and the U.S. EPA National Center for Computational Toxicology
    Elaine A Cohen Hubal
    National Center for Computational Toxicology, US Environmental Protection Agency, Research Triangle Park, North Carolina 27711, USA
    J Expo Sci Environ Epidemiol 20:231-6. 2010
    ..In addition, common themes inherent throughout National Center for Computational Toxicology research activities are highlighted for emphasis as exposure science advances into the 21st century...
  6. ncbi Simulating microdosimetry in a virtual hepatic lobule
    John Wambaugh
    National Center for Computational Toxicology, Office of Research and Development, U S Environmental Protection Agency, Research Triangle Park, North Carolina, United States of America
    PLoS Comput Biol 6:e1000756. 2010
    ..The mass-balanced graphical approach to modeling the hepatic lobule is computationally efficient for simulating long-term exposure, modular for incorporating complex cellular interactions, and flexible for dealing with evolving tissues...
  7. ncbi In vitro perturbations of targets in cancer hallmark processes predict rodent chemical carcinogenesis
    Nicole C Kleinstreuer
    National Center for Computational Toxicology, Office of Research and Development, US Environmental Protection Agency, Research Triangle Park, North Carolina 27711, USA
    Toxicol Sci 131:40-55. 2013
    ..This model represents a chemical carcinogenicity prioritization tool supporting targeted testing and functional validation of cancer pathways...
  8. ncbi Using pathway modules as targets for assay development in xenobiotic screening
    Richard S Judson
    National Center for Computational Toxicology, Office of Research and Development, US Environmental Protection Agency, Research Triangle Park, NC 27711, USA
    Mol Biosyst 8:531-42. 2012
    ..These selected genes could then form the basis for a battery to test for pathway-chemical interactions under many biological contexts using throughput expression-based assays...
  9. ncbi Systems toxicology from genes to organs
    John Jack
    U S Environmental Protection Agency, Research Triangle Park, NC, USA
    Methods Mol Biol 930:375-97. 2013
    ....
  10. ncbi Simulating quantitative cellular responses using asynchronous threshold Boolean network ensembles
    John Jack
    National Center for Computational Toxicology, Office of Research and Development, US Environmental Protection Agency, Research Triangle Park, North Carolina, USA
    BMC Syst Biol 5:109. 2011
    ..This results in noisy but highly reproducible aggregate level responses that are consistent with experimental data...
  11. ncbi A comparison of machine learning algorithms for chemical toxicity classification using a simulated multi-scale data model
    Richard Judson
    National Center for Computational Toxicology, Office of Research and Development, US Environmental Protection Agency, Research Triangle Park, North Carolina 27711, USA
    BMC Bioinformatics 9:241. 2008
    ..We present a novel model to simulate complex chemical-toxicology data sets and use this model to evaluate the relative performance of different machine learning (ML) methods...