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Drug Discovery

27 papers with code · Medical

Drug discovery is the task of applying machine learning to discover new candidate drugs.

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Greatest papers with code

Atomic Convolutional Networks for Predicting Protein-Ligand Binding Affinity

30 Mar 2017deepchem/deepchem

The atomic convolutional neural network is trained to predict the experimentally determined binding affinity of a protein-ligand complex by direct calculation of the energy associated with the complex, protein, and ligand given the crystal structure of the binding pose.

DRUG DISCOVERY

Self-Normalizing Neural Networks

NeurIPS 2017 bioinf-jku/SNNs

We introduce self-normalizing neural networks (SNNs) to enable high-level abstract representations.

DRUG DISCOVERY PULSAR PREDICTION

Neural Message Passing for Quantum Chemistry

ICML 2017 Microsoft/gated-graph-neural-network-samples

Supervised learning on molecules has incredible potential to be useful in chemistry, drug discovery, and materials science.

DRUG DISCOVERY NODE CLASSIFICATION

Gated Graph Sequence Neural Networks

17 Nov 2015Microsoft/gated-graph-neural-network-samples

Graph-structured data appears frequently in domains including chemistry, natural language semantics, social networks, and knowledge bases.

#2 best model for SQL-to-Text on WikiSQL

DRUG DISCOVERY NODE CLASSIFICATION SQL-TO-TEXT

An Overview of Multi-Task Learning in Deep Neural Networks

15 Jun 2017HazyResearch/metal

Multi-task learning (MTL) has led to successes in many applications of machine learning, from natural language processing and speech recognition to computer vision and drug discovery.

DRUG DISCOVERY MULTI-TASK LEARNING SPEECH RECOGNITION

Molecular Sets (MOSES): A Benchmarking Platform for Molecular Generation Models

29 Nov 2018molecularsets/moses

Deep generative models such as generative adversarial networks, variational autoencoders, and autoregressive models are rapidly growing in popularity for the discovery of new molecules and materials.

DRUG DISCOVERY

Junction Tree Variational Autoencoder for Molecular Graph Generation

ICML 2018 wengong-jin/icml18-jtnn

We evaluate our model on multiple tasks ranging from molecular generation to optimization.

DRUG DISCOVERY

ChemGAN challenge for drug discovery: can AI reproduce natural chemical diversity?

28 Aug 2017mostafachatillon/ChemGAN-challenge

In this paper, we quantify this internal chemical diversity, and we raise the following challenge: can a nontrivial AI model reproduce natural chemical diversity for desired molecules?

DRUG DISCOVERY

Ligand Pose Optimization with Atomic Grid-Based Convolutional Neural Networks

20 Oct 2017gnina/gnina

Docking is an important tool in computational drug discovery that aims to predict the binding pose of a ligand to a target protein through a combination of pose scoring and optimization.

DRUG DISCOVERY