Article

A New Advanced <em>In silico</em> Drug Discovery Method for Novel Coronavirus (SARS-CoV-2) with Tensor Decomposition-based Unsupervised Feature Extraction

2020-06-03

Abstract excerpt

<h4>Background: </h4> COVID-19 is a critical pandemic that has affected human communities worldwide, and there is an urgent need to develop effective drugs. Although there are a large number of candidate drug compounds that may be useful for treating COVID-19, the evaluation of these drugs is time-consuming and costly. Thus, screening to identify potentially effective drugs prior to experimental validation is nece...

Topics

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

Identifiers and source

Literature Corpus work: e690e20a-bd5b-57ff-9d43-4c6c7cb94cb3
DOI: 10.20944/preprints202004.0524.v2

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

A New Advanced <em>In silico</em> Drug Discovery Method for Novel Coronavirus (SARS-CoV-2) with Tensor Decomposition-based Unsupervised Feature ExtractionDOI 10.20944/preprints202004.0524.v2Read

Novel Method for Detection of Genes With Altered Expression Caused by Coronavirus Infection and Screening of Candidate Drugs for SARS-CoV-2Semantic proximity Read

TDbasedUFE and TDbasedUFEadv: bioconductor packages to perform tensor decomposition based unsupervised feature extractionSemantic proximity Read

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 Read

Universal nature of drug treatment responses in drug-tissue-wide model-animal experiments using tensor decomposition-based unsupervised feature extractionSemantic proximity Read

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 Read

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

Neurological disorder drug discovery from gene expression with tensor decompositionSemantic proximity Read

Computational Approaches to Assist Drug Repositioning for COVID-19Semantic proximity Read

A New Approach to Drug Repurposing with Two-Stage Prediction, Machine Learning, and Unsupervised Clustering of Gene ExpressionSemantic proximity Read

Tensor-based machine learning for multi-omics integrative clustering and feature discoverySemantic proximity Read

Identifying Transcriptomic Signatures and Rules for SARS-CoV-2 InfectionSemantic proximity Read

Tensor decomposition-Based Unsupervised Feature Extraction Applied to Single-Cell Gene Expression AnalysisSemantic proximity Read