There are 4 repositories under toxicology topic.
Write reproducible code for getting and processing ChEMBL
Health Assessment Workspace Collaborative, a content management system for systematic reviews
The eNanoMapper ontology
Data-driven chemical-induced toxicity prediction by machine learning using chemical and bioactivity data
R package for simulation of caffeine concentration <doi:10.12793/tcp.2017.25.3.141>. https://asancpt.github.io/caffsim
R Shiny App to Visualize and Summarize Repeat-Dose Toxicology Study Results
The rebirth of IMPACT World+ in a fully automated and transparent fashion.
A query engine to retrive information from AOP wiki graph database.
Repository to coordinate the work of the Toxicology Community.
SARAlerts is a code to generate structural alerts (toxic alerts) using Local Interpretable Model-Agnostic Explanations (LIME) of machine learning models from Tox21, Clintox, and Sider datasets.
OpenRiskNet pipeline for TGX case study: toxicology predictions based on transcriptomic profiles
links related to SEND/Nonclinical toxicology
ANDA: An open-source tool for automated image analysis of in vitro neuronal cells
Molecular structure-based classification of chemicals in known hazard groups
BBBP Explainer is a code to generate structural alerts of blood-brain barrier penetrating and non-penetrating drugs using Local Interpretable Model-Agnostic Explanations (LIME) of machine learning models from BBBP dataset.
OpenTox functionality for Bioclipse.
[Frontend] A knowledge graph system with graph neural network for drug discovery, disease mechanism and biomarker screening.
This Python project uses neural networks and genetic algorithms to design bioinsecticide compounds targeting specific proteins. By leveraging IC50 values from FASTA sequences, it generates and optimizes SMILES representations, enhancing the efficacy and specificity of bioinsecticides.
U.S. EPA Benchmark Dose Modeling Software User Interface (BMDS Desktop and BMDS Online)
Endocrine Disruption Explainer is a code to generate structural alerts of endocrine disruption of chemcial compounds using Local Interpretable Model-Agnostic Explanations (LIME) of machine learning models from TOX-21, EDC, and EDKB-FDA datasets.
My personal website, served at https://cthoyt.com
workshop materials for "A hands-on introduction to applied artificial intelligence in toxicology"
Data and code for rodent hepatotoxicity prediction
Run the AMBIT services on Docker
A Python module for analysis and visualization of dose-response data
A meteor-based table-building application for epidemiology, and mechanistic data used in the human-health assessment of chemicals.
Mutagen Explainer is a code to generate structural alerts of mutagenicity of chemcial compounds using Local Interpretable Model-Agnostic Explanations (LIME) of machine learning models from Bursi and Hansen Ames mutagenicity datasets.
An adverse drug reaction (ADR) is described by the World Health Organization (WHO) as a 'response to a medicine which is noxious and unintended, and which occurs at doses normally used in man
SMaRt: A Toxicity Classification System through SMILES and Multimodal Representation to Cross-check Hazardous Chemicals
The public version of the 'XploreAOP' Shiny application to interactively visualize AOP Networks
Source code for the web application associated with "Transformers enable accurate prediction of acute and chronic chemical toxicity in aquatic organisms".