Back to search

Article

Novel artificial intelligence-based identification of drug-gene-disease interaction using protein-protein interaction

2024-06-03

Abstract excerpt

The evaluation of drug-gene-disease interactions is key for the identification of drugs effective against disease. However, at present, drugs that are effective against genes that are critical for disease are difficult to identify. Following a disease-centric approach, there is a need to identify genes critical to disease function and find drugs that are effective against them. By contrast, following a drug-centri...

Topics

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

Identifiers and source

Literature Corpus work
2cf5d456-23f0-59c4-8c4b-4a43a728c119
DOI
10.1101/2024.06.01.596984
Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest
Interactive article relationship graphSelect a related publication card to move it into the centre and load its closest explainable connections. Solid lines are source-backed structured connections. Dashed lines are semantic discovery signals and are not scientific evidence.
Novel artificial intelligence-based identification of drug-gene-disease interaction using protein-protein interactionDOI 10.1101/2024.06.01.596984
Identification of Candidate Drugs for Heart Failure using Tensor Decomposition-Based Unsupervised Feature Extraction Applied to Integrated Analysis of Gene Expression between Heart Failure and DrugMatrix DatasetsSemantic proximity
Universal nature of drug treatment responses in drug-tissue-wide model-animal experiments using tensor decomposition-based unsupervised feature extractionSemantic proximity
Novel Method for Detection of Genes With Altered Expression Caused by Coronavirus Infection and Screening of Candidate Drugs for SARS-CoV-2Semantic proximity
Tensor decomposition- and principal component analysis-based unsupervised feature extraction to select more reasonable differentially expressed genes: Optimization of standard deviation versus state-of-art methodsSemantic proximity
A New Advanced <em>In silico</em> Drug Discovery Method for Novel Coronavirus (SARS-CoV-2) with Tensor Decomposition-based Unsupervised Feature ExtractionSemantic proximity
TDbasedUFE and TDbasedUFEadv: bioconductor packages to perform tensor decomposition based unsupervised feature extractionSemantic proximity
Neurological disorder drug discovery from gene expression with tensor decompositionSemantic proximity
A New Approach to Drug Repurposing with Two-Stage Prediction, Machine Learning, and Unsupervised Clustering of Gene ExpressionSemantic proximity
Systematic drug repositioning for a wide range of diseases with integrative analyses of phenotypic and molecular data.Semantic proximity
Prioritization of Potential Drugs Through Pathway-Based Drug Repurposing and Network Proximity AnalysisSemantic proximity
Artificial intelligence based computational framework for drug-target prioritization and inference of novel repositionable drugs for Alzheimer’s diseaseSemantic proximity
Tensor decomposition-Based Unsupervised Feature Extraction Applied to Single-Cell Gene Expression AnalysisSemantic proximity
Select a neighboring publication to make it the new centre.