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biwalklda

brwmc

BRWMC: Predicting lncRNA-disease associations based on Bi-random walk and matrix completion on disease and lncRNA networks

brwmdi

BRWMDI is a computational method to identify potential microbe-disease interactions.

deep-drm

egatmda

etgpda

ETGPDA: identification of piRNA-disease associations based on embedding transformation graph convolutional network

evalne

Source code for EvalNE, a Python library for evaluating Network Embedding methods.

gacnnmda-gsamda-mdad

GACNNMDA: a computational model for predicting potential human microbe-drug associations based on graph attention network and CNN-based classifier

gcmdr

IMPLEMENT FOR graph convolution for predicting associations between miRNA and drug resistance using raw data

genedr

Gene based message passing for drug repurposing

graph-regularized-nnmf

Graph-Regularized Non-Negative Matrix Factorization on Manifold

grgmf

grnmf

An R/Rcpp/RcppArmadillo implementation of Deng Cai's Non-negative Matrix Factorization on Manifold, sometimes called GNMF or GrNMF.

knowledge_graph_attention_network

KGAT: Knowledge Graph Attention Network for Recommendation, KDD2019

lagcn

Code and Datasets for "Predicting Drug-Disease Associations through Layer Attention Graph Convolutional Networks"

lda-lnsubrw

lncRNA-disease association prediction based on linear neighborhood similarity and unbalanced bi-random walk

lncrna-disease-methods

m2dminers

A toolbox for predicting miRNA-disease associations

mahn_liuwenzhi

Predicting disease-metabolite associations based on the metapath aggregation of tripartite heterogeneous networks

med_text

medical text processing

mhrwr

Package: MHRWR Type: Package Title: MHRWR Prediction of lncRNA-disease associations based on multiple heterogeneous networks ================= Description: This package implements the MHRWR algorithm based on multiple heterogeneous networks, predicting lncRNA-disease associations. Files: 1.Dataset 1) LncFunGauSim.txt, DisSemGauSim.txt and GeneLls

microbe-drug-disease

Predicting pairwise relationships between human microbes, drugs and diseases

mirna-disease-association-prediction

Using MATLAB predicting miRNA–disease association based with KATZ and RW

ninimhmda

NinimHMDA, a graph convolutional neural network model for large-scale multiple types human microbe-disease association prediction

ntsmda

pcstii

rbf_keras

RBF layer for Keras

rbf_nn_tensorflow

RBF neural network was constructed using tensorflow framework

rwr-project

Random Walk with Restart project from math course M2 DLAD

rwrhn-ff

A random-walk with restart algorithm over an enriched graph constructed using type-2 fuzzy data fusion.