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de_novo_design_rnn

Code for "De novo molecular design with chemical language models"

deep_learning_coronavirus_cure

Using deep learning to generate novel molecules as candidates for binding with coronavirus protease

deep_learning_examples

Examples of using deep learning in Bioinformatics

deep_scaffold

deepram

End-to-end deep learning toolkit for predicting protein binding sites and motifs.

deeprank

Deep Learning for the ranking of protein-protein conformations

deepred

deepscreen

DEEPScreen: Virtual Screening with Deep Convolutional Neural Networks Using Compound Images

deepsea

Similarity Ensemble Approach with deep learning substance fingerprints

deepsequence

A generative latent variable model for biological sequence families.

deepsmiles

DeepSMILES - A variant of SMILES for use in machine-learning

deepsurf

A surface-based deep learning approach for the prediction of ligand binding sites on proteins

deeptoxic

top 1% solution to toxic comment classification challenge on Kaggle.

deepvs

Boosting Docking-Based Virtual Screening with Deep Learning

defined_proteins

The DEFINED-PROTEINS software package allows users to: (i) derive descriptor of elementary functions of interest directly from protein structures; (ii) use derived descriptor in rational design and protein engineering of protein functions.

defmap

DEFMap: Dynamics Extraction From cryo-em Map

delinker

deltavina

DeltaVina scoring function

denovodesignofbioactiveproteinswitches

Code used in the manuscript for De Novo Design of Bioactive Protein Switches

deploying-machine-learning-models

Example Repo for the Udemy Course "Deployment of Machine Learning Models"

desc_mol-ddie

Implementation of Using Drug Descriptions and Molecular Structures for Drug-Drug Interaction Extraction from Literature

descriptastorus

Descriptor computation(chemistry) and (optional) storage for machine learning

deviumweb

Interactive multivariate data analysis in R implemented in shiny.

dgl-ke

High performance, easy-to-use, and scalable package for learning large-scale knowledge graph embeddings.

dgraphdta

a novel DTA predition method using graph neural network

dialib

Automated generation of theoretical ion library of peptides and glycopeptides for data independent analysis

diffxpy

Differential expression analysis for single-cell RNA-seq data.

dig

A library for graph deep learning research

digital-patient

dimenet

DimeNet and DimeNet++ models, as proposed in "Directional Message Passing for Molecular Graphs" (ICLR 2020) and "Fast and Uncertainty-Aware Directional Message Passing for Non-Equilibrium Molecules" (NeurIPS-W 2020)