Development of Novel Computational Tools

The broad range of models developed and used in the group include approaches from applied mathematics, machine learning, cheminformatics, Bayesian statistics, and quantum chemistry.

We utilize a number of computer languages and software tools in our research to develop specialized tools, conduct simulations, carry out data processing, and perform visualizations. These languages and applications include python, R, MATLAB, NetLogo, MCSim, TensorFlow, scikit-learn, Smoldyn, CompuCell3D, MCell and CellBlender, Gaussian, MOPAC, GROMACS, RDKit, Monolix Suite.

Some of the specialized tools we have developed are described below.

kc-hits

The computational package kc-hits 1 productivity-enhancing tool for the diverse scientists and agencies involved in classifying chemicals for their carcinogenic potential.

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DoseSim

The computational package DoseSim 2 is useful in characterizing biomarkers and conducting dose estimation for various chemicals, including the organophosphorus insecticide, chlorpyrifos.

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BioTRaNS

BioTRaNS 3 (Biochemical Tool for Reaction Network Simulation) is a package for a software package for computational xenobiotic metabolomics It has the capability to predict the metabolite inventory and pathways resulting from exposure to chemicals and mixtures of chemicals.

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PoPKAT

Work is underway to develop a user-friendly software platform for population physiologically-based pharmacokinetic (PBPK) modeling The software is called PoPKAT (Population PBPK Analysis Toolkit) and the initial application will be targeted at assessing bioequivalence for generic drugs.

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1

https://doi.org/10.1093/bioinformatics/btac189

2

https://www.ncbi.nlm.nih.gov/pubmed/23162056

3

https://www.ncbi.nlm.nih.gov/pubmed/16086453