rnaimehaom Goto Github PK

graph-based-molecule-generation-using-gan

graph-convolutional-network-for-esol

This is an implementation and explanation of Graph Neural Networks for predicting water solubility of small organic molecules based on their chemical composition and structural information in PyTorch Geometric

graph-embeddings

Graph and Nodes embeddings for downstream tasks

graph-neural-networks-for-drug-discovery

graph-nvp

GraphNVP: An Invertible Flow Model for Generating Molecular Graphs

graph2smiles

graph2vec

A parallel implementation of "graph2vec: Learning Distributed Representations of Graphs" (MLGWorkshop 2017).

graph_convolutional_network

Predicting solubility of a molecule in water using graph convolutional networks

graph_convolutional_network_chemical_property

graphaf

graphchem

Graph-based machine learning for chemical property prediction

graphdeesmartcontract

Smart contract vulnerability detection using graph neural network (DR-GCN).

graphdg

Generative model for molecular distance geometry

graphdta

GraphDTA: Predicting drug-target binding affinity with graph neural networks

graphdti

graphein

Protein Graph Library

graphinvent

Graph neural networks for molecular design.

graphkit-learn

A python package for graph kernels, graph edit distances, and graph pre-image problem.

graphml-tutorials

Tutorials for Machine Learning on Graphs

graphmvp

graphormer

Graphormer is a deep learning package that allows researchers and developers to train custom models for molecule modeling tasks. It aims to accelerate the research and application in AI for molecule science, such as material design, drug discovery, etc.

graphretro

Learning Graph Models for Retrosynthesis Prediction (NeurIPS 2021)

graphrnn

Graph Generative Model (Pytorch implementation)

graphrxn

GraphRXN

graphsim

R package: Simulate Expression data from igraph network using mvtnorm (CRAN; JOSS)

graphsol

Code of our JC paper: "Structure-aware protein solubility prediction from sequence through graph convolutional network and predicted contact map"

graphsolmol

Repository contains the python code for a undergraduate research project on aqueous solubility modelling using vectorial and graphical kernels for SVM.

graphsynth

With GraphSynth, one can design, implement, test, and automatically invoke grammar rules that transform a graph from an initial seed into a creative design.

graphvae_approx

Efficient Learning of Non-Autoregressive Graph Variational Autoencoders for Molecular Graph Generation

graphvae_compress

Compressed Graph Representation for Scalable Molecular Graph Generation