52 Repositories
Python drug-pair 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
DeepStruc is a Conditional Variational Autoencoder which can predict the mono-metallic nanoparticle from a Pair Distribution Function.
ChemRxiv | [Paper] XXX DeepStruc Welcome to DeepStruc, a Deep Generative Model (DGM) that learns the relation between PDF and atomic structure and the
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.
UUID_ApiGenerator - This an API that will return a key-value pair of randomly generated UUID
This an API that will return a key-value pair of randomly generated UUID. Key will be a timestamp and value will be UUID. While the
A simple API that will return a key-value pair of randomly generated UUID
A simple API that will return a key-value pair of randomly generated UUID. Key will be a timestamp and value will be UUID. While the server is running, whenever the API is called, it should return all the previous UUIDs ever generated by the API alongside a new UUID.
Source code for our CVPR 2019 paper - PPGNet: Learning Point-Pair Graph for Line Segment Detection
PPGNet: Learning Point-Pair Graph for Line Segment Detection PyTorch implementation of our CVPR 2019 paper: PPGNet: Learning Point-Pair Graph for Line
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
Alcarin Tengwar - a Tengwar typeface designed to pair well with the Brill typeface
Alcarin Tengwar Alcarin Tengwar is a Tengwar typeface designed to pair well with
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
Using Bert as the backbone model for lime, designed for NLP task explanation (sentence pair text classification task)
Lime Comparing deep contextualized model for sentences highlighting task. In addition, take the classic explanation model "LIME" with bert-base model
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
Self-adjusting, auto-compounding multi-pair DCA crypto trading bot using Python, AWS Lambda & 3Commas API
Self-adjusting, auto-compounding multi-pair DCA crypto trading bot using Python, AWS Lambda & 3Commas API The following code describes how we can leve
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
Trans-Encoder: Unsupervised sentence-pair modelling through self- and mutual-distillations
Trans-Encoder: Unsupervised sentence-pair modelling through self- and mutual-distillations Code repo for paper Trans-Encoder: Unsupervised sentence-pa
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
Fusion 360 Add-in that creates a pair of toothed curves that can be used to split a body and create two pieces that slide and lock together.
Fusion-360-Add-In-PuzzleSpline Fusion 360 Add-in that creates a pair of toothed curves that can be used to split a body and create two pieces that sli
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
Guess Your Card - A Multiplayer Python Game
Guess Your Card - A Multiplayer Python Game This is a guessing card game having two levels - Developed in Python and can be played between two to four
A program will generate a eth key pair that has the public key that starts with a defined amount of 0
ETHAdressGenerator This short program will generate a eth key pair that has the public key that starts with a defined amount of 0 Requirements Python
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
Random JSON Key:Pair Json Generator
Random JSON Key:Value Pair Generator This simple script take an engish dictionary of words and and makes random key value pairs. The dictionary has ap
BPEmb is a collection of pre-trained subword embeddings in 275 languages, based on Byte-Pair Encoding (BPE) and trained on Wikipedia.
BPEmb is a collection of pre-trained subword embeddings in 275 languages, based on Byte-Pair Encoding (BPE) and trained on Wikipedia. Its intended use is as input for neural models in natural language processing.
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
Scalable Attentive Sentence-Pair Modeling via Distilled Sentence Embedding (AAAI 2020) - PyTorch Implementation
Scalable Attentive Sentence-Pair Modeling via Distilled Sentence Embedding PyTorch implementation for the Scalable Attentive Sentence-Pair Modeling vi
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.
Using deep actor-critic model to learn best strategies in pair trading
Deep-Reinforcement-Learning-in-Stock-Trading Using deep actor-critic model to learn best strategies in pair trading Abstract Partially observed Markov
Official repository for "PAIR: Planning and Iterative Refinement in Pre-trained Transformers for Long Text Generation"
pair-emnlp2020 Official repository for the paper: Xinyu Hua and Lu Wang: PAIR: Planning and Iterative Refinement in Pre-trained Transformers for Long
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
Pool funds to bootstrap a Uniswap pair
Seed liquidity A contract to pool funds which are then used to boostrap a new Uniswap liquidity pair. Specification A new SeedLiquidity contract is de