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Drug Discovery

32 papers with code · Medical

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

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Molecule Property Prediction Based on Spatial Graph Embedding

Journal of Chemical Information and Modeling 2019 wxfsd/C-SGEN

And, multiple C-SGELs are stacked to construct a convolution spatial graph embedding network (C-SGEN) for end-to-end representation learning.

 SOTA for Graph Regression on Lipophilicity (RMSE metric )

DRUG DISCOVERY GRAPH EMBEDDING GRAPH REGRESSION

0
22 Aug 2019

Attention-based Multi-Input Deep Learning Architecture for Biological Activity Prediction: An Application in EGFR Inhibitors

12 Jun 2019lehgtrung/egfr-att

These data were trained on a deep learning model which was also integrated with the Attention mechanism to facilitate training and interpreting.

ACTIVITY PREDICTION DRUG DISCOVERY

6
12 Jun 2019

Relational Dose-Response Modeling for Cancer Drug Studies

10 Jun 2019tansey/functionalmf

Exploratory cancer drug studies test multiple tumor cell lines against multiple candidate drugs.

DENOISING DRUG DISCOVERY IMPUTATION

2
10 Jun 2019

DeeplyTough: Learning Structural Comparison of Protein Binding Sites

bioRxiv 2019 BenevolentAI/DeeplyTough

Protein binding site comparison (pocket matching) is of importance in drug discovery.

DRUG DISCOVERY

25
05 Apr 2019

Interpretable Deep Learning in Drug Discovery

7 Mar 2019bioinf-jku/interpretable_ml_drug_discovery

Without any means of interpretation, neural networks that predict molecular properties and bioactivities are merely black boxes.

DRUG DISCOVERY

18
07 Mar 2019

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.

BENCHMARKING DRUG DISCOVERY

225
29 Nov 2018

GuacaMol: Benchmarking Models for De Novo Molecular Design

22 Nov 2018benevolentAI/guacamol

De novo design seeks to generate molecules with required property profiles by virtual design-make-test cycles.

BENCHMARKING DRUG DISCOVERY

85
22 Nov 2018

KekuleScope: prediction of cancer cell line sensitivity and compound potency using convolutional neural networks trained on compound images

22 Nov 2018isidroc/kekulescope

We show that the predictive power of the generated models is comparable to that of Random Forest (RF) models and fully-connected Deep Neural Networks trained on circular (Morgan) fingerprints.

DRUG DISCOVERY PREDICTION OF CANCER CELL LINE SENSITIVITY

4
22 Nov 2018

CheMixNet: Mixed DNN Architectures for Predicting Chemical Properties using Multiple Molecular Representations

14 Nov 2018paularindam/CheMixNet

SMILES is a linear representation of chemical structures which encodes the connection table, and the stereochemistry of a molecule as a line of text with a grammar structure denoting atoms, bonds, rings and chains, and this information can be used to predict chemical properties.

DRUG DISCOVERY

7
14 Nov 2018