qsar
There are 4 repositories under qsar topic.
kexinhuang12345 / DeepPurpose
A Deep Learning Toolkit for DTI, Drug Property, PPI, DDI, Protein Function Prediction (Bioinformatics)
Language:Jupyter Notebook 933Mariewelt / OpenChem
OpenChem: Deep Learning toolkit for Computational Chemistry and Drug Design Research
Language:Python 667- Language:Jupyter Notebook 343
ml-jku / clamp
Code for the paper Enhancing Activity Prediction Models in Drug Discovery with the Ability to Understand Human Language
Language:Python 81dosorio / Peptides
An R package to calculate indices and theoretical physicochemical properties of peptides and protein sequences.
Language:R 76MolecularAI / QSARtuna
QSARtuna: QSAR model building with the optuna framework
Language:Jupyter Notebook 58PaccMann / chemical_representation_learning_for_toxicity_prediction
Chemical representation learning paper in Digital Discovery
Language:Jupyter Notebook 49- QSPRpredLanguage:Jupyter Notebook 35
martin-sicho / genui
The backend services of the GenUI framework. The backend provides the REST API used for molecular generation, QSAR modelling and chemical space visualization.
Language:Python 30ersilia-os / zaira-chem
Automated QSAR based on multiple small molecule descriptors
Language:Python 26Ishan-Kumar2 / Molecular_VAE_Pytorch
PyTorch implementation of the paper "Automatic Chemical Design Using a Data-Driven Continuous Representation of Molecules"
Language:Python 25patonlab / wSterimol
Generate Boltzmann-weighted Sterimol Steric Parameters for Conformationally-Flexible Substituents
Language:Python 25jeffrichardchemistry / pyADA
A cheminformatics package to perform Applicability Domain of molecular fingerprints based in similarity calculation.
Language:Jupyter Notebook 21- Language:Python 20
- automated-qsar-framework
LabMolUFG / automated-qsar-framework
Automated framework for the curation of chemogenomics data and to develop QSAR models for virtual screening using the open-source KNIME software
GenUI frontend application. It provides a GUI to the GenUI REST API web services.
Language:JavaScript 18UnixJunkie / molenc
MolEnc: a molecular encoder using rdkit and OCaml.
Language:OCaml 18drug-design / course
drugdesign.org source of truth
- Language:Python 13
plissonf / ML-guided-discovery-and-design-of-non-hemolytic-peptides
Classification models for hemolytic nature and hemolytic activity predictions in peptide/protein sequences
Language:Jupyter Notebook 13Simple web application for prediction of reaction rate constant through machine learning models using molecular fingerprints.
Language:Python 12david-leon / HAG-Net
Code for "Enhance Information Propagation for Graph Neural Network by Heterogeneous Aggregations"
Language:Python 10Application for detecting functional groups of a molecules.
Language:Python 9alvesvm / sars-cov-mpro
QSAR models and putative agents identified against SARS-CoV-2
Language:Jupyter Notebook 8scads-biochem / LigEGFR
LigEGFR: Spatial graph embedding and molecular descriptors assisted bioactivity prediction of ligand molecules for epidermal growth factor receptor on a cell line-based dataset
ashiwoku / QSAR-model
This repository contains a QSAR model that predicts the ability of a chemical compound to inhibit the gene associated with Alzheimer's, Beta-Secratese 1
Language:Jupyter Notebook 7hargrove-lab / QSAR
The diversity of RNA structural elements and their documented role in human diseases make RNA an attractive therapeutic target. However, progress in drug discovery and development has been hindered by challenges in the determination of high-resolution RNA structures and a limited understanding of the parameters that drive RNA recognition by small molecules, including a lack of validated quantitative structure-activity relationships (QSAR). Herein, we developed QSAR models that quantitatively predict both thermodynamic and kinetic-based binding parameters of small molecules and the HIV-1 TAR model system. Small molecules bearing diverse scaffolds was screened against the HIV-1 TAR using surface plasmon resonance. Then multiple linear regression (MLR) combined with feature selection was performed to afford robust models that allowed direct interpretation of properties critical for both binding strength and kinetic rate constants. These models were externally validated with new molecules and their accurate performance confirmed via comparison to ensemble tree methods.
Language:R 7A package to perform fingerprints from spectroscopy datas.
Language:Jupyter Notebook 7rongma6 / QSARMPC_DTIMPC
Secure multiparty computation for privacy-preserving drug discovery
Language:Python 7Reference implementation of the Distance-Based Boolean Applicability Domain for HTS datasets
Language:OCaml 7Henrique-rt / QSAR_applicability_domain_convex_hull
Allows to visualize and analyze if the molecules of the test set and of an external set are contained in the convex hull defined by the molecules of the training set.
Language:Python 6A 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.
Language:Shell 6Reference implementation of the Vanishing Ranking Kernels (VRK) method
Language:OCaml 6Wishartlab-openscience / Biotransformer
A computational tool for the prediction and identification of metabolites.
Language:Java 6NikhilMukraj / mod-qsar
A modular inverse QSAR pipeline
Language:Python 5
