Reinforcement learning environments for drug discovery
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Updated
May 23, 2024 - Jupyter Notebook
Reinforcement learning environments for drug discovery
Message Passing Neural Networks for Molecule Property Prediction
Design of target-focused libraries by probing continuous fingerprint space with recurrent neural networks. The repository accompanies a research paper which is currently under review (08.04.24)
Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology
This repository is the collection point of reference data for the GPCRdb. The GPCRdb contains reference data, interactive visualisation and experiment design tools for G protein-coupled receptors (GPCRs).
Protwis is the backbone of the GPCRdb. The GPCRdb contains reference data, interactive visualisation and experiment design tools for G protein-coupled receptors (GPCRs).
Open Targets python framework for post-GWAS analysis
Statistical analysis of the PLATCOV trial
Therapeutics Commons: Artificial Intelligence Foundation for Therapeutic Science
A common data access layer for AI-driven drug discovery.
Official implementation of DrugGEN
SELFormer: Molecular Representation Learning via SELFIES Language Models
Introduction to Applied Mathematics and Informatics in Drug Discovery (AMIDD)
An interoperable Python framework for biomolecular simulation.
My personal website, served at https://cthoyt.com
Code to accompany the "Implications of Topological Imbalance for Representation Learning on Biomedical Knowledge Graphs" (Briefings in Bioinformatics, 2022)
Code to accompany the "Understanding the Performance of Knowledge Graph Embeddings in Drug Discovery" manuscript (Artificial Intelligence in the Life Sciences, 2022)
De Novo Drug Design
Python-based GUI to collect Feedback of Chemist in Molecules
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