Postdoctoral Profiles

John Jack, Ph.D.

Computational Analysis and Modeling, Louisiana Tech University
Postdoctoral Fellow, EPA's National Center for Computational Toxicology

As a postdoctoral researcher in the NCCT, I have opportunities to collaborate with a diverse group of talented scientists.  I enjoy using these collaborations to fuel my research into the molecular pathways underlying hepatotoxicity.  I am grateful for the outstanding mentorship available at the NCCT coupled with the chance to pursue environmentally inspired problems in  systems biology.

Virtual Liver Project
The U.S. EPA Virtual Liver Project (v-Liver™) is aimed at producing an innovative computational system for estimating the effects of environmental contaminants in the human liver. Current approaches for assessing the risk of chemical-induced liver toxicity are based on results of animal testing, which are difficult to extrapolate to humans. To address this challenge we are developing "Virtual Tissues" -- a multidisciplinary approach that integrates data from in vitro experiments into in silico  microanatomic models of tissues. The v-Liver™ is a proof-of-concept model of the hepatic lobule, the anatomic unit of the liver. Our goal is to use  molecular and cellular in vitro data  from ToxCast™ and public domain information to elucidate and simulate the key processes involved in Nuclear Receptor (NR)-mediated liver cancer. In the long-term,  v-Liver™ will reduce dependence on animal testing through predictive tools for estimating the risk of chronic liver injury in humans.

Jimena L. Davis, Ph.D.

Computational Mathematics, North Carolina State University
Cross ORD Postdoctoral Fellow, EPA's National Center for Computational Toxicology

I enjoy collaborating with so many talented disciplinary scientists in NCCT in efforts that will address critical issues in human health. Being able to utilize and further develop my computational and analytical skills while working on interesting yet challenging biological applications that are essential to the health of others is very rewarding and what I enjoy most about my work.

Quantifying Uncertainty in Linked Exposure-to-Effects Models for Pyrethroid Pesticides
With the increased use of models in describing the metabolism and distribution of toxins in humans, quantifying the uncertainty in the estimates of unknown model parameters as well as model predictions has become an increasingly important yet complex task due to the various levels of uncertainty (e.g., uncertainty in parameter estimates and model extrapolations) that must be considered. Variability must also be accounted for accurately since some model parameters vary across individuals within a population. In an effort to provide better quantitative assessments of the effects of toxins on human health, we are working on the development of computational and statistical methodologies for quantifying the variability and uncertainty of predictions from linked quantitative models describing exposure, internal dose, and biological effects. The methodologies developed in this cross-disciplinary research project will be useful not only in the cumulative risk assessments for pyrethroid pesticides but will also provide better standards for future cumulative risk assessments.

Nicole C. Kleinstreuer, Ph.D.

Biomedical Engineer, University of Canterbury
Postdoctoral Fellow, EPA's National Center for Computational Toxicology

It is a privilege and an honor to work at NCCT with a group of highly motivated, intelligent individuals. I am inspired by the mentoring and guidance I receive, and by the numerous opportunities for collaboration and cooperative learning. My work on computational modeling of embryonic vasculogenesis/angiogenesis is very challenging and rewarding, and aspires to elucidate a deeper understanding of human developmental toxicity pathways.

Virtual Embryo Project
Nicole Kleinstreuer is working on computational modeling and analysis of microvascular networks in EPA's Virtual Embryo. The Virtual Embryo project proposes to construct an agent-based model of microvascular network formation during early limb-bud development, to characterize these computational models by incorporating biological pathways for normal embryonic development and ToxCast predictive signatures, and to perform a functional analysis of causal linkages leading from pathway-level targets to chemical mode-of-action processes in abnormal development.

Holly M. Mortensen, Ph.D.

Biology, University of Maryland, College Park
Cross ORD Postdoctoral Fellow, EPA's National Center for Computational Toxicology

I enjoy using interdisciplinary approaches in solving complex biological problems with direct application to human health. I am inspired by working with the experts at the NCCT who are from very diverse scientific backgrounds, a composition that is essential in order to appropriately address complex human health issues.

The U.S. Environmental Protection Agency (EPA), through its ToxCast program, is developing predictive toxicity approaches that will use in vitro high-throughput screening (HTS), high-content screening (HCS) and toxicogenomic data to predict in vivo toxicity phenotypes. To help analyze the ToxCast data, which is generated from over 600 different assays, we are developing a platform to infer predictive toxicological signatures. Among other features, this platform will provide a visually intuitive representation, using network inference, of quantitative chemical effects across multiple levels of biological organization, including relationships to in vivo toxicity endpoints. We will use these methods to visualize the genes and pathways that are activated by environmental chemicals, in order to help set priorities for further testing. By linking specific chemicals to their genes and corresponding disease states, we will be able to generate useful hypotheses concerning differential risk across population groups, and in turn contribute to the larger goals of clarifying the role of gene-environment interaction in disease states.

Nisha Sipes, Ph.D.

Cancer and Cell Biology, University of Cincinnati
Postdoctoral Fellow, EPA's National Center for Computational Toxicology

I am drawn to exciting new challenges, which is why I am here at the EPA. NCCT integrates knowledge and skills from high caliber professionals (both in and out of the Agency) for the difficult challenge of predictive toxicology. I enjoy all aspects of this postdoctoral position, from the open collaborations, integration of biological and computational approaches, learning new techniques, and last but certainly not least the environmental focus of our work.

Virtual Embryo Project
The v-Embryo™ Project is focused on improving the predictive capabilities of in vitro toxicity testing through the application of in silico models with sufficient depth and detail for predictive modeling of developmental defects. The project aims to integrate ToxCast™ high-throughput screening (HTS) data with vast knowledge of developmental cell signaling pathways and computer-generated simulations of morphogenesis using agent-based modeling (ABM) approaches. To accomplish this, I will focus my research efforts on ABM models utilizing cell signaling pathways important to processes such as cell adhesion, migration, growth and differentiation. By simulating the normal development, we hope to gain insight about the critical network state relations and dynamical responses of the system to local perturbations, modeling altered system development with the signature profiles generated from HTS data.

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