Article

Comprehensive analysis of pathways in Coronavirus 2019 (COVID-19) using an unsupervised machine learning method

2022-05-19

Abstract excerpt

The World Health Organization (WHO) introduced “Coronavirus disease 19” or “COVID-19” as a novel coronavirus in March 2020. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) requires the fast discovery of effective treatments to fight this worldwide crisis. Artificial intelligence and bioinformatics analysis pipelines can assist with finding biomarkers, explanations, and cures. Artificial intelligence a...

Topics

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

Identifiers and source

Literature Corpus work: 13d6d5cd-1c89-5870-bb99-0eb1f1cdcc22
DOI: 10.1101/2022.05.18.492441

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Comprehensive analysis of pathways in Coronavirus 2019 (COVID-19) using an unsupervised machine learning methodDOI 10.1101/2022.05.18.492441Read

Using unsupervised learning algorithms to identify essential genes associated with SARS-CoV-2 as potential therapeutic targets for COVID-19Semantic proximity Read

Identification of genes and signaling pathways associated with severe COVID-19: high-throughput data analysis with a system virology approachSemantic proximity Read

Bioinformatics and machine learning approach identifies potential drug targets and pathways in COVID-19Semantic proximity Read

A Novel 3-Gene Signature for Identifying COVID-19 Patients Based on Bioinformatics and Machine LearningSemantic proximity Read

Identification of essential genes associated with SARS-CoV-2 infection as potential drug target candidates with machine learning algorithmsSemantic proximity Read

Deciphering Novel SARS CoV-2 specific Disease Pathways from RNA Sequencing Data of COVID-19 Infected A549 Cells and Potential Therapeutics using Next Generation Knowledge Discovery PlatformsSemantic proximity Read

PCA-based unsupervised feature extraction for gene expression analysis of COVID-19 patients.Semantic proximity Read

Pathway Expression AnalysisSemantic proximity Read

Automated machine learning optimizes and accelerates predictive modeling from COVID-19 high throughput datasetsSemantic proximity Read

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

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

XGBoost-Based Feature Learning Method for Mining COVID-19 Novel Diagnostic MarkersSemantic proximity Read