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Comprehensive pathway enrichment analysis workflows: COVID-19 case study. (Specia Issue: Bioinformatics helping to mitigate the impact of COVID-19.)
Briefings in Bioinformatics ; 22(2):676-689, 2021.
Article in English | CAB Abstracts | ID: covidwho-1343646
ABSTRACT
The coronavirus disease 2019 (COVID-19) outbreak due to the novel coronavirus named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been classified as a pandemic disease by the World Health Organization on the 12th March 2020. This world-wide crisis created an urgent need to identify effective countermeasures against SARS-CoV-2. In silico methods, artificial intelligence and bioinformatics analysis pipelines provide effective and useful infrastructure for comprehensive interrogation and interpretation of available data, helping to find biomarkers, explainable models and eventually cures. One class of such tools, pathway enrichment analysis (PEA) methods, helps researchers to find possible key targets present in biological pathways of host cells that are targeted by SARS-CoV-2. Since many software tools are available, it is not easy for non-computational users to choose the best one for their needs. In this paper, we highlight how to choose the most suitable PEA method based on the type of COVID-19 data to analyze. We aim to provide a comprehensive overview of PEA techniques and the tools that implement them.

Full text: Available Collection: Databases of international organizations Database: CAB Abstracts Type of study: Case report / Experimental Studies Language: English Journal: Briefings in Bioinformatics Year: 2021 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: CAB Abstracts Type of study: Case report / Experimental Studies Language: English Journal: Briefings in Bioinformatics Year: 2021 Document Type: Article