astrazeneca Goto Github PK
Name: AstraZeneca
Type: Organization
Bio: Data and AI: Unlocking new science insights
Location: Global
Name: AstraZeneca
Type: Organization
Bio: Data and AI: Unlocking new science insights
Location: Global
The goal of arrayedCRISPRscreener is to simulate arrayed CRISPR screening data for the purpose of benchmarking data analysis tools as well as power calculation.
A collection of research papers, datasets and software related to knowledge graphs for drug discovery. Accompanies the paper "A review of biomedical datasets relating to drug discovery: a knowledge graph perspective" (Briefings in Bioinformatics, 2022)
Readings for "A Unified View of Relational Deep Learning for Drug Pair Scoring." (IJCAI 2022)
A collection of research papers and software related to explainability in graph machine learning.
Reading list for "The Shapley Value in Machine Learning" (JCAI 2022)
learning biology syllabus, geared for machine learning folks
Code to accompany the "Implications of Topological Imbalance for Representation Learning on Biomedical Knowledge Graphs" (Briefings in Bioinformatics, 2022)
A PyTorch and TorchDrug based deep learning library for drug pair scoring. (KDD 2022)
Tensorflow-Keras implementation of deep Convolutional Capsule Networks with Dynamic Routing algorithm
Clinical Trial Enrollment Life Cycle (CTELC) modeling project aims to leverage "industry-wide" data to understand key drivers and build predictive models. Patient attrition, also referred to as dropout or patient withdrawal, occurs when patients enrolled in a clinical trial either withdraw or are lost to follow-up by the clinical site and trial sponsor.
A pipeline to rapidly detect exogenous DNA integration sites using DNA or RNA paired-end sequencing data
Improved clinical data imputation via classical and quantum determinantal point processes
gene interaction matrices, a novel approach to using ConvNets on gene expression data
Implement Go/No-Go policies using multiple endpoints, and simulate the outcome under different scenarios.
Implementation of the SGNN graph neural network for 1H and 13C NMR prediction and a tool for distinguishing different molecules based on HSQC simulations
We trained high performing open source models on image scans of tissue biopsies to predict endoscopic categories in inflammatory bowel disease. These predictive models can help us better understand the disease pathology and represent a step towards automated clinical recruitment strategies.
This is a shiny tool to classify and analyse pre-clinical tumour data automatically.
Fast calculation of hydrogen-bond strengths and free energy of hydration of small molecules.
Forecasting for knowable future events using Bayesian informative priors (forecasting with judgmental-adjustment).
Efficiently calculate 3D-features for quantitative structure-activity relationship approaches.
Fast, world class biomedical NER
Code to accompany the "Understanding the Performance of Knowledge Graph Embeddings in Drug Discovery" manuscript (Artificial Intelligence in the Life Sciences, 2022)
The code was developed for training diverse ML and DL models to predict PROTACs degradation. Data cleaning for two public datasets, PROTAC-DB and PROTACpedia, are also included. PROTACs are of high interest for all disease areas of AZ and thus predicting their degradation is of general interest.
Extensions packages for magnus
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.