ricardoamferreira / Predicting-Adverse-Drug-Reactions-with-Machine-Learning
The objective of this work is to develop machine learning (ML) methods that can accurately predict adverse drug reactions (ADRs) using the databases SIDER and OFFSIDES.
☆24Updated last year
Alternatives and similar repositories for Predicting-Adverse-Drug-Reactions-with-Machine-Learning:
Users that are interested in Predicting-Adverse-Drug-Reactions-with-Machine-Learning are comparing it to the libraries listed below
- Introduction to Applied Mathematics and Informatics in Drug Discovery (AMIDD)☆30Updated 3 months ago
- A high throughput automated drug discovery pipeline.☆29Updated 7 years ago
- Mol2vec notebooks for use with Binder service☆29Updated 7 years ago
- Machine learning guided association of adverse drug reactions with in vitro off-target pharmacology☆33Updated 4 years ago
- Open Drug Metabolism & PharmacoKinetics (OpenDMPK) is an open source data resource and toolkit for predicting drug metabolism and pharmac…☆25Updated 3 years ago
- ChemSpaceAL: An Efficient Active Learning Methodology Applied to Protein-Specific Molecular Generation☆16Updated last year
- Houses deployable code for the SCORCH scoring function and docking pipeline from the related publication: https://doi.org/10.1016/j.jare.…☆17Updated 2 years ago
- An Integrative Drug Repurposing Pipeline using KNIME and Programmatic Data Access: A case study on COVID-19 Data☆14Updated 4 years ago
- Python implementation of common ADME properties.☆34Updated 2 years ago
- My (small) research project in solubility of drug-like molecules☆18Updated 4 years ago
- MzDOCK - An Automated GUI based pipeline for Molecular Docking☆17Updated last month
- Prediction of compound synthesis accessibility bashed on reaction knowledge graph☆18Updated 2 years ago
- TargetDB is a tool to quickly querry multiple publicly available databases and provide an integrated view of the information available ab…☆32Updated 8 months ago
- StarGazer is a tool designed for rapidly assessing drug repositioning opportunities. It combines multi-source, multi-omics data with a no…☆34Updated last year
- Computational Analysis of Novel Drug Opportunities☆36Updated last month
- Perform probe-guided blind docking with FTMap and DOCK6☆10Updated last year
- A computational drug discovery project, in which bioinformatic and machine learning tools are used to identify possible molecular targets…☆21Updated 4 years ago
- Deep-learning models for Drug Discovery and Quantum Chemistry☆27Updated 7 years ago
- ☆17Updated 4 years ago
- Improved Scaffold Hopping in Ligand-based Virtual Screening Using Neural Representation Learning☆21Updated 4 years ago
- ☆16Updated 2 years ago
- Multiobjective De Novo Drug Design with Recurrent Neural Networks and Nondominated Sorting☆18Updated 5 years ago
- Synthetic Accessible Prediction of Organic Compounds based on Graph Attention Mechanism☆20Updated last year
- Code for "De novo molecular design with chemical language models"☆13Updated 3 years ago
- Source code and data files for manuscript titled "Pharmaceutical patent landscaping: A novel approach to understand patents from the drug…☆13Updated last year
- Machine Learning Projects☆24Updated 5 years ago
- Automated framework for the curation of chemogenomics data and to develop QSAR models for virtual screening using the open-source KNIME s…☆20Updated 4 years ago
- ABC of chemoinformatics☆18Updated 6 years ago
- Tutorial on the usage of Rdkit, Pandas, sklearn, machine learning, descriptor calculation, etc.. in the context of bioactivity predictive…☆14Updated 10 years ago
- Python package is for paper 'Predicting potential drug-drug interactions by integrating chemical, biological, phenotypic and network data…☆34Updated 8 years ago