A Deep Learning Toolkit for DTI, Drug Property, PPI, DDI, Protein Function Prediction (Bioinformatics)
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Updated
Oct 30, 2023 - Jupyter Notebook
A Deep Learning Toolkit for DTI, Drug Property, PPI, DDI, Protein Function Prediction (Bioinformatics)
Deep Reinforcement Learning for de-novo Drug Design
OpenChem: Deep Learning toolkit for Computational Chemistry and Drug Design Research
An R package to calculate indices and theoretical physicochemical properties of peptides and protein sequences.
Chemical representation learning paper in Digital Discovery
Modeling framework for eTRANSAFE project
Generate Boltzmann-weighted Sterimol Steric Parameters for Conformationally-Flexible Substituents
The backend services of the GenUI framework. The backend provides the REST API used for molecular generation, QSAR modelling and chemical space visualization.
PyTorch implementation of the paper "Automatic Chemical Design Using a Data-Driven Continuous Representation of Molecules"
Classification models for hemolytic nature and hemolytic activity predictions in peptide/protein sequences
A high-quality hand-curated logD7.4 dataset of 1,130 compounds
A cheminformatics package to perform Applicability Domain of molecular fingerprints based in similarity calculation.
Automated QSAR based on multiple small molecule descriptors
QSARtuna: QSAR model building with the optuna framework
Calculate Sterimol Parameters from Sructure Input/Output Files
A tool for creating Quantitative Structure Property Relationship (QSPR) models.
GenUI frontend application. It provides a GUI to the GenUI REST API web services.
Automated framework for the curation of chemogenomics data and to develop QSAR models for virtual screening using the open-source KNIME software
Code for the paper Enhancing Activity Prediction Models in Drug Discovery with the Ability to Understand Human Language
A repository to build and deploy GenUI docker images. GenUI is a collection of web services for interactive molecular generation, QSAR modelling and chemical space visualization.
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