Article

Graph convolutional network learning model based on new integrated data of the protein-protein interaction network and network pharmacology for the prediction of herbal medicines effective for the treatment of metabolic diseases

2024-04-30

Abstract excerpt

Chronic metabolic diseases constitute a group of conditions requiring long-term management and hold significant importance for national public health and medical care. Currently, in Korean medicine, there are no insurance-covered herbal prescriptions designated primarily for the treatment of metabolic diseases. Therefore, the objective of this study was to identify herbal prescriptions from the existing pool of in...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: cc87e3cf-5fa4-5de9-9e19-09611a2453ed
DOI: 10.1101/2024.04.24.591043

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Graph convolutional network learning model based on new integrated data of the protein-protein interaction network and network pharmacology for the prediction of herbal medicines effective for the treatment of metabolic diseasesDOI 10.1101/2024.04.24.591043Read

Network Analysis of Predicted Therapeutic Symptoms in National Health Insurance Herbal PrescriptionsSemantic proximity Read

Identification of bioactive constituents for colitis from traditional Chinese medicine prescription via deep neural networkSemantic proximity Read

Drug Components-Disease Network Related to Acute Lung Injury Inference Based on Forest Graph-embedded Deep Feedforward NetworkSemantic proximity Read

Emerging Drug Combinations for Targeting Tongue Neoplasms Associated Proteins/Genes: Employing Graph Neural Networks within the RAIN ProtocolSemantic proximity Read

Repurposing Drugs for COVID-19 by Graph Convolutional NetworkSemantic proximity Read

TCMPR: TCM Prescription Recommendation Based on Subnetwork Term Mapping and Deep Learning.Semantic proximity Read

Network-guided supervised learning on gene expression using a graph convolutional neural networkSemantic proximity Read

Repurposing Non-pharmacological Interventions for Alzheimer’s Diseases through Link Prediction on Biomedical LiteratureSemantic proximity Read

A knowledge graph approach to discovering drug combination therapies across the phenomeSemantic proximity Read

Graph Attention Networks for Drug Combination Discovery: Targeting Pancreatic Cancer Genes with RAIN ProtocolSemantic proximity Read

UniGEN-DDI: Computing drug-drug interactions using a unified graph embedding networkSemantic proximity Read

Evaluating The Effectiveness Of Graph Convolutional Network For Detection Of Polypharmacy Side EffectsSemantic proximity Read