| Literature DB >> 34902125 |
Angela Serra1,2,3, Luca Cattelani1,2,3, Michele Fratello1,2,3, Vittorio Fortino4, Pia Anneli Sofia Kinaret1,2,3,5, Dario Greco6,7,8,9.
Abstract
Biomarkers are valuable indicators of the state of a biological system. Microarray technology has been extensively used to identify biomarkers and build computational predictive models for disease prognosis, drug sensitivity and toxicity evaluations. Activation biomarkers can be used to understand the underlying signaling cascades, mechanisms of action and biological cross talk. Biomarker detection from microarray data requires several considerations both from the biological and computational points of view. In this chapter, we describe the main methodology used in biomarkers discovery and predictive modeling and we address some of the related challenges. Moreover, we discuss biomarker validation and give some insights into multiomics strategies for biomarker detection.Entities:
Keywords: Biological validation; Biomarker; Classifier; Data unbalancing; Feature selection; Hyperparameter estimation; Microarray; Model selection; Multiomics; Validation metrics
Mesh:
Substances:
Year: 2022 PMID: 34902125 DOI: 10.1007/978-1-0716-1839-4_8
Source DB: PubMed Journal: Methods Mol Biol ISSN: 1064-3745