35 Repositories
Python drug-repurposing Libraries
OOD Dataset Curator and Benchmark for AI-aided Drug Discovery
ðĨ DrugOOD ðĨ : OOD Dataset Curator and Benchmark for AI Aided Drug Discovery This is the official implementation of the DrugOOD project, this is the
Jupyter Dock is a set of Jupyter Notebooks for performing molecular docking protocols interactively, as well as visualizing, converting file formats and analyzing the results.
Molecular Docking integrated in Jupyter Notebooks Description | Citation | Installation | Examples | Limitations | License Table of content Descriptio
TigerLily: Finding drug interactions in silico with the Graph.
Drug Interaction Prediction with Tigerlily Documentation | Example Notebook | Youtube Video | Project Report Tigerlily is a TigerGraph based system de
Repository for "Improving evidential deep learning via multi-task learning," published in AAAI2022
Improving evidential deep learning via multi task learning It is a repository of AAAI2022 paper, âImproving evidential deep learning via multi-task le
EquiBind: Geometric Deep Learning for Drug Binding Structure Prediction
EquiBind: geometric deep learning for fast predictions of the 3D structure in which a small molecule binds to a protein
GeneDisco is a benchmark suite for evaluating active learning algorithms for experimental design in drug discovery.
GeneDisco is a benchmark suite for evaluating active learning algorithms for experimental design in drug discovery.
Drug prediction
I have collected data about a set of patients, all of whom suffered from the same illness. During their course of treatment, each patient responded to one of 5 medications, Drug A, Drug B, Drug c, Drug x and y. Part of our job is to build a model to find out which drug might be appropriate for a future patient with the same illness. The feature sets of this dataset are Age, Sex, Blood Pressure, and Cholesterol of patients, and the target is the drug that each patient responded to.
ð A 3D Generative Model for Structure-Based Drug Design (NeurIPS 2021)
A 3D Generative Model for Structure-Based Drug Design Coming soon... Citation @inproceedings{luo2021sbdd, title={A 3D Generative Model for Structu
NLP techniques such as named entity recognition, sentiment analysis, topic modeling, text classification with Python to predict sentiment and rating of drug from user reviews.
This file contains the following documents sumbited for Baruch CIS9665 group 9 fall 2021. 1. Dataset: drug_reviews.csv 2. python codes for text classi
Natural Language Processing for Adverse Drug Reaction (ADR) Detection
Natural Language Processing for Adverse Drug Reaction (ADR) Detection This repo contains code from a project to identify ADRs in discharge summaries a
NeoDTI: Neural integration of neighbor information from a heterogeneous network for discovering new drug-target interactions
NeoDTI NeoDTI: Neural integration of neighbor information from a heterogeneous network for discovering new drug-target interactions (Bioinformatics).
The code for SAG-DTA: Prediction of DrugâTarget Affinity Using Self-Attention Graph Network.
SAG-DTA The code is the implementation for the paper 'SAG-DTA: Prediction of DrugâTarget Affinity Using Self-Attention Graph Network'. Requirements py
A PyTorch based deep learning library for drug pair scoring.
Documentation | External Resources | Datasets | Examples ChemicalX is a deep learning library for drug-drug interaction, polypharmacy side effect and
Systemic Evolutionary Chemical Space Exploration for Drug Discovery
SECSE SECSE: Systemic Evolutionary Chemical Space Explorer Chemical space exploration is a major task of the hit-finding process during the pursuit of
Rapid experimentation and scaling of deep learning models on molecular and crystal graphs.
LitMatter A template for rapid experimentation and scaling deep learning models on molecular and crystal graphs. How to use Clone this repository and
Molecular Sets (MOSES): A Benchmarking Platform for Molecular Generation Models
Molecular Sets (MOSES): A benchmarking platform for molecular generation models Deep generative models are rapidly becoming popular for the discovery
Multi-modal co-attention for drug-target interaction annotation and Its Application to SARS-CoV-2
CoaDTI Multi-modal co-attention for drug-target interaction annotation and Its Application to SARS-CoV-2 Abstract Environment The test was conducted i
A Python package to process & model ChEMBL data.
insilico: A Python package to process & model ChEMBL data. ChEMBL is a manually curated chemical database of bioactive molecules with drug-like proper
Readings for "A Unified View of Relational Deep Learning for Polypharmacy Side Effect, Combination Therapy, and Drug-Drug Interaction Prediction."
Polypharmacy - DDI - Synergy Survey The Survey Paper This repository accompanies our survey paper A Unified View of Relational Deep Learning for Polyp
Drug Discovery App Using Lipinski's Rule-of-Five.
Drug Discovery App A Drug Discovery App Using Lipinski's Rule-of-Five. TAPIWA CHAMBOKO ð About Me I'm a full stack developer experienced in deploying
Readings for "A Unified View of Relational Deep Learning for Polypharmacy Side Effect, Combination Therapy, and Drug-Drug Interaction Prediction."
Polypharmacy - DDI - Synergy Survey The Survey Paper This repository accompanies our survey paper A Unified View of Relational Deep Learning for Polyp
Visualization Data Drug in thailand during 2014 to 2020
Visualization Data Drug in thailand during 2014 to 2020 Data sorce from āļāđāļāļĄāļđāļĨāđāļāļīāļāļ āļēāļāļĢāļąāļ āļŠāļģāļāļąāļāļāļēāļ āļ.āļ.āļŠ Inttroducing program Using tkinter module for
Deep generative models of 3D grids for structure-based drug discovery
What is liGAN? liGAN is a research codebase for training and evaluating deep generative models for de novo drug design based on 3D atomic density grid
Using Clinical Drug Representations for Improving Mortality and Length of Stay Predictions
Using Clinical Drug Representations for Improving Mortality and Length of Stay Predictions Usage Clone the code to local. https://github.com/tanlab/MI
grungegirl is the hacker's drug encyclopedia. programmed in python for maximum modularity and ease of configuration.
grungegirl. cli-based drug search for girls. welcome. grungegirl is aiming to be the premier drug culture application. it is the hacker's encyclopedia
TorchDrug is a PyTorch-based machine learning toolbox designed for drug discovery
A powerful and flexible machine learning platform for drug discovery
Drug design and development team HackBio internship is a virtual bioinformatics program that introduces students and professional to advanced practical bioinformatics and its applications globally.
-Nyokong. Drug design and development team HackBio internship is a virtual bioinformatics program that introduces students and professional to advance
A central task in drug discovery is searching, screening, and organizing large chemical databases
A central task in drug discovery is searching, screening, and organizing large chemical databases. Here, we implement clustering on molecular similarity. We support multiple methods to provide a interactive exploration of chemical space.
Fast and scalable uncertainty quantification for neural molecular property prediction, accelerated optimization, and guided virtual screening.
Evidential Deep Learning for Guided Molecular Property Prediction and Discovery Ava Soleimany*, Alexander Amini*, Samuel Goldman*, Daniela Rus, Sangee
Cancer Drug Response Prediction via a Hybrid Graph Convolutional Network
DeepCDR Cancer Drug Response Prediction via a Hybrid Graph Convolutional Network This work has been accepted to ECCB2020 and was also published in the
This is the repo for the paper `SumGNN: Multi-typed Drug Interaction Prediction via Efficient Knowledge Graph Summarization'. (published in Bioinformatics'21)
SumGNN: Multi-typed Drug Interaction Prediction via Efficient Knowledge Graph Summarization This is the code for our paper ``SumGNN: Multi-typed Drug
Datamol is a python library to work with molecules
Datamol is a python library to work with molecules. It's a layer built on top of RDKit and aims to be as light as possible.
Structural basis for solubility in protein expression systems
Structural basis for solubility in protein expression systems Large-scale protein production for biotechnology and biopharmaceutical applications rely
Datamol is a python library to work with molecules.
Datamol is a python library to work with molecules. It's a layer built on top of RDKit and aims to be as light as possible.
Optimising chemical reactions using machine learning
Summit Summit is a set of tools for optimising chemical processes. Weâve started by targeting reactions. What is Summit? Currently, reaction optimisat