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.
☆23Updated 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
- A high throughput automated drug discovery pipeline.☆29Updated 6 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
- ChemSpaceAL: An Efficient Active Learning Methodology Applied to Protein-Specific Molecular Generation☆15Updated last year
- A computational drug discovery project, in which bioinformatic and machine learning tools are used to identify possible molecular targets…☆20Updated 3 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
- An Integrative Drug Repurposing Pipeline using KNIME and Programmatic Data Access: A case study on COVID-19 Data☆14Updated 4 years ago
- Introduction to Applied Mathematics and Informatics in Drug Discovery (AMIDD)☆29Updated last month
- Mol2vec notebooks for use with Binder service☆29Updated 6 years ago
- Machine learning guided association of adverse drug reactions with in vitro off-target pharmacology☆33Updated 4 years ago
- Drug discovery project by making use of the Tox-21 dataset.☆16Updated last year
- Deep-learning models for Drug Discovery and Quantum Chemistry☆27Updated 7 years ago
- A Graph Neural Network Model for prediction of the effectiveness of a drug on a given cancer cell lines☆17Updated last year
- MzDOCK - An Automated GUI based pipeline for Molecular Docking☆11Updated last month
- StarGazer is a tool designed for rapidly assessing drug repositioning opportunities. It combines multi-source, multi-omics data with a no…☆32Updated last year
- ABC of chemoinformatics☆18Updated 6 years ago
- Multiobjective De Novo Drug Design with Recurrent Neural Networks and Nondominated Sorting☆18Updated 4 years ago
- comparing drug classification methods☆19Updated 4 years ago
- Prediction of compound synthesis accessibility bashed on reaction knowledge graph☆16Updated 2 years ago
- Computational Analysis of Novel Drug Opportunities☆35Updated this week
- Learning protein representation for rigid-body docking☆22Updated 5 years ago
- My (small) research project in solubility of drug-like molecules☆18Updated 4 years ago
- Multi-Channel Deep Chemogenomic Modeling of Receptor-Ligand Binding Affinity Prediction for Drug Discovery☆27Updated 3 years ago
- Model to predict kinase-ligand pKi values.☆12Updated last year
- Tutorial on the usage of Rdkit, Pandas, sklearn, machine learning, descriptor calculation, etc.. in the context of bioactivity predictive…☆14Updated 10 years ago
- Improved Scaffold Hopping in Ligand-based Virtual Screening Using Neural Representation Learning☆21Updated 3 years ago
- A package for MD, Docking and Machine learning drug discovery pipeline☆42Updated 4 years ago
- code for Zagidullin et al 2021 "Comparative analysis of molecular fingerprints in prediction of drug combination effects"☆16Updated 2 years ago
- Machine Learning Projects☆23Updated 5 years ago
- A Data-Driven Approach to Predicting Successes and Failures of Clinical Trials☆18Updated 5 years ago
- ☆9Updated 5 years ago