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Differential gene expression analysis pipelines and bioinformatic tools for the identification of specific biomarkers: A review

Authors :
Diletta Rosati
Maria Palmieri
Giulia Brunelli
Andrea Morrione
Francesco Iannelli
Elisa Frullanti
Antonio Giordano
Source :
Computational and Structural Biotechnology Journal, Vol 23, Iss , Pp 1154-1168 (2024)
Publication Year :
2024
Publisher :
Elsevier, 2024.

Abstract

In recent years, the role of bioinformatics and computational biology together with omics techniques and transcriptomics has gained tremendous importance in biomedicine and healthcare, particularly for the identification of biomarkers for precision medicine and drug discovery. Differential gene expression (DGE) analysis is one of the most used techniques for RNA-sequencing (RNA-seq) data analysis. This tool, which is typically used in various RNA-seq data processing applications, allows the identification of differentially expressed genes across two or more sample sets. Functional enrichment analyses can then be performed to annotate and contextualize the resulting gene lists. These studies provide valuable information about disease-causing biological processes and can help in identifying molecular targets for novel therapies. This review focuses on differential gene expression (DGE) analysis pipelines and bioinformatic techniques commonly used to identify specific biomarkers and discuss the advantages and disadvantages of these techniques.

Details

Language :
English
ISSN :
20010370
Volume :
23
Issue :
1154-1168
Database :
Directory of Open Access Journals
Journal :
Computational and Structural Biotechnology Journal
Publication Type :
Academic Journal
Accession number :
edsdoj.f64c519b55ef476e9353a0ff34a17e73
Document Type :
article
Full Text :
https://doi.org/10.1016/j.csbj.2024.02.018