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codon_optimization_app

Calculate %MaxMin of rare codon clusters

coevolveml

Deploying synthetic coevolution and machine learning to engineer protein-protein interactions

constrained-graph-variational-autoencoder

Sample code for Constrained Graph Variational Autoencoders

controlled-peptide-generation

source code for https://arxiv.org/abs/2005.11248 "Accelerating Antimicrobial Discovery with Controllable Deep Generative Models and Molecular Dynamics"

cpi_hgcn

Predicting Compound-Protein Interaction using Hierarchical Graph Convolutional Networks

cs224w_winter2021

CS224W Stanford Winter 2021 Homework solutions

cs236_dgm

🦍 Stanford CS236 : Deep Generative Models

cse-250a-probabilistic

dask-tutorial

Dask tutorial

decimer-image_transformer

DECIMER 2.0: Deep Learning for Chemical Image Recognition using Efficient-Net V2 + Transformer

deep-clathrin

Identification of clathrin proteins by incorporating hyperparameter optimization in deep learning and PSSM profiles

deep-learning-slow-modes

Supporting data for the manuscript "Deep learning the slow modes for rare events sampling"

deep_learning_symmetries

deepchem

Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology

deepdock

Code related to : O. Mendez-Lucio, M. Ahmad, E.A. del Rio-Chanona, J.K. Wegner, A Geometric Deep Learning Approach to Predict Binding Conformations of Bioactive Molecules

deepmind-research

This repository contains implementations and illustrative code to accompany DeepMind publications

deepmscnn

deep learning for mutational analysis

deeprank-gnn

Graph Network for protein-protein interface

denss

Calculate electron density from a solution scattering profile

dgn

Implementation of Directional Graph Networks in PyTorch and DGL

dl4chem-mgm

druidom

DRUIDom (DRUg Interacting Domains): a computational method for predicting new drug/compound - target protein interactions for drug discovery and repurposing, via mapping ligands to structural domains

dsressol

DSResSol: A sequence-based solubility predictor created with Dilated Squeeze Excitation Residual Networks

ecnet

An evolutionary context-integrated deep learning framework for protein engineering

eegsde

This is the official implementation for Equivariant Enengy-guided SDE for Inverse Molecule Design (ICLR 2023)

egnn

Energetic GraphNeural Networks (EGNN) implementation based on Dirichlet Energy Constrained Learning.

egnn-1

egnn-pytorch

Implementation of E(n)-Equivariant Graph Neural Networks, in Pytorch

enhancing-enzyme-solubility

equibind

EquiBind: geometric deep learning for fast predictions of the 3D structure in which a small molecule binds to a protein