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tox_data

Collect datasets for computational toxicology

tox_models

Package of predictive models for targets of toxicological interest to the HeCaToS project.

toxcast_valueeval_for_ml_modeling_dili_ebtc_analysis

Evaluation of value added by Toxcast assay "read-outs" to prediction of DILI/hepatoxicity class of pharmaceutical drugs

toxdl

ToxDL: Toxicity predictor with deep learning

toxeval

The toxEval R-package includes a set of functions to analyze, visualize, and organize measured concentration data as it relates to chosen biological effects benchmarks. See http://usgs-r.github.io/toxEval for more details

toxibtl

Code for paper "ToxIBTL: prediction of peptide toxicity based on information bottleneck and transfer learning"

toxicity

toxicity-classification

toxicity-classification-1

https://www.kaggle.com/c/jigsaw-unintended-bias-in-toxicity-classification

toxicity-prediction

Collection of machine learning models for predicting toxicity of molecules

toxicity-prediction-gcn

A Graph convolution neural network based toxicity prediction, project of SJTU-CS410 Artificial Intelligence(B),2020 Fall

toxicity_prediction

toxicity_prediction_challenge

Predicting whether chemicals are toxic or not by using the best machine learning model.

toxicitymodel

Computational hazard assessment of MeOx nanoparticle toxicity using machine learning

toxicitypredictionchallenge

With new chemicals being synthesized every day, toxicity prediction of newly synthesized chemicals is mandatory before they could be released in the market. For a long time, *in-vivo* methods have been used for toxicity prediction which involves studying bacteria, human cells, or animals. With thousands of new chemicals being synthesized every day, it is not feasible to detect toxicity with traditional laboratory animal testing. One great alternative for *in-vivo *methods is the *in-silico* techniques that have great potential to reduce time, cost, and animal testing involved in detecting toxicity. ToxCast dataset is one of the greatest data available in the field of toxicogenomics. ToxCast has data for approximately 9,000 chemicals with more than 1500 high-throughput assay endpoints that cover a range of high-level cell responses. In this challenge, you will have access to a prepared subset of data from ToxCast.

toxicogx

A statistical package, in R, used in cancer research to analyze toxicity of drugs on cancer gene expression across large-scale toxicogenomic datasets.

toxicophore

toxicr

toxigen

This repo contains the code for generating the ToxiGen dataset, published at ACL 2022.

toxim

ToxiM: A Toxicity Prediction Tool for Small Molecules

toxsmi

Toxicity prediction models

toxtree

ToxTree is a machine learning based model to predict hERG and Nav1.5 cardiotoxicity of a molecular compound at the outset of drug development process.

toy-md

Python code for learning Molecular Dynamics simulations

tpo_qsar

tr-rosetta-pytorch

Implementation of trRosetta and trDesign for Pytorch, made into a convenient package, for protein structure prediction and design

tracer

Posterior summarisation in Bayesian phylogenetics

training-collection

Collection of bioinformatics training materials

transfer-learning-library

Transfer Learning Library for Domain Adaptation, Task Adaptation, and Domain Generalization

transfer-learning-molecular-design

transfomercpi2.0

Drug design and repurposing with a sequence-to-drug paradigm, doi: https://doi.org/10.1101/2022.03.26.485909