Data-driven chemical-induced toxicity prediction by machine learning using chemical and bioactivity data
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Updated
Feb 7, 2017 - Jupyter Notebook
Data-driven chemical-induced toxicity prediction by machine learning using chemical and bioactivity data
Gestion documentaire en toxicologie
R scripts and data used to produce the "Genotoxic Evaluation of Mexican Welders Occupationally Exposed to Welding-Fumes Using the Micronucleus Test on Exfoliated Oral Mucosa Cells: A Case-Control Study" paper
OpenTox functionality for Bioclipse.
Molecular structure-based classification of chemicals in known hazard groups
Toxicology Screening Selection (Rest API) 2.1.2
Workflows for prediction of inhalation toxicokinetics from chemical structure including the individual steps in the training and optimization of QSPR models, model selection and prediction of partition coefficients, applicability domain and toxicokinetics profile.
Guide for the Baccarelli Lab GitHub
OpenRiskNet pipeline for TGX case study: toxicology predictions based on transcriptomic profiles
examples of data analyses for toxicology
Fully working version
Data and code for rodent hepatotoxicity prediction
Prioritization of agents for cancer hazard assessments
R package for simulation of caffeine concentration <doi:10.12793/tcp.2017.25.3.141>. https://asancpt.github.io/caffsim
This repo contains code and presentations used for ad-hoc analyses regarding liver cell toxicology and development. It also contains analyses on human and mice immune cells.
This is a folder for my M.S. Thesis related information.
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