Editorial: Application of bioinformatics, machine learning, and artificial intelligence to improve diagnosis, prognosis and treatment of cancer

Vidović, Tinka; Ozretić, Petar (2026) Editorial: Application of bioinformatics, machine learning, and artificial intelligence to improve diagnosis, prognosis and treatment of cancer. Frontiers in Aging, 6 . ISSN 2673-6217

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Abstract

In recent years, omics approaches have yielded great advances in cancer research and have provided new in-depth insights into the processes involved in cancer development and progression. Practical use of the information contained within this huge amount of data requires computational approaches such as bioinformatics, machine learning (ML), and artificial intelligence (AI). These computational methods, together with omics data from large databases, such as The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO), can now be used to develop cancer biomarkers, novel anti-cancer drug targets, and both novel and repurposed treatment options for cancer. Considering the application of versatile computational methods in cancer research, we collected original research articles in this Research Topic to present the novel discovery of potential cancer drug targets, prognostic biomarkers, or therapeutic interventions.

Item Type:	Article
Uncontrolled Keywords:	cancer biomarkers; cancer diagnosis and therapy; cancer drug targets; computational cancer biology; computational drug discovery; artificial intelligence; bioinformatics; machine learning
Subjects:	NATURAL SCIENCES > Biology > Biochemistry and Molecular Biology BIOMEDICINE AND HEALTHCARE > Basic Medical Sciences BIOTECHNICAL SCIENCES > Biotechnology > Bioinformatics
Divisions:	Division of Molecular Medicine
Depositing User:	Ema Buhin Šaler
Date Deposited:	05 Feb 2026 15:27
URI:	http://fulir.irb.hr/id/eprint/11221
DOI:	10.3389/fragi.2025.1763491

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