Supervised Methods for Biomarker Detection from Microarray Experiments

Research output: Chapter in Book/Report/Conference proceedingChapterScientificpeer-review

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.

Original languageEnglish
Title of host publicationMicroarray Data Analysis
EditorsGiuseppe Agapito
PublisherHumana Press
Pages101-120
Number of pages20
ISBN (Electronic)978-1-0716-1839-4
ISBN (Print)978-1-0716-1841-7
DOIs
Publication statusPublished - 2022
Publication typeA3 Part of a book or another research book

Publication series

NameMethods in Molecular Biology
Volume2401
ISSN (Print)1064-3745
ISSN (Electronic)1940-6029

Keywords

  • Biological validation
  • Biomarker
  • Classifier
  • Data unbalancing
  • Feature selection
  • Hyperparameter estimation
  • Microarray
  • Model selection
  • Multiomics
  • Validation metrics

Publication forum classification

  • Publication forum level 1

ASJC Scopus subject areas

  • Molecular Biology
  • Genetics

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