Literature DB >> 34902125

Supervised Methods for Biomarker Detection from Microarray Experiments.

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.
© 2022. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.

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


  50 in total

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Journal:  Methods Mol Biol       Date:  2010

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Review 3.  What are biomarkers?

Authors:  Kyle Strimbu; Jorge A Tavel
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Review 4.  A review of feature selection techniques in bioinformatics.

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5.  An Ensemble Feature Selection Method for Biomarker Discovery.

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Journal:  Proc IEEE Int Symp Signal Proc Inf Tech       Date:  2018-06-21

Review 6.  Challenges and opportunities for oncology biomarker discovery.

Authors:  Avisek Deyati; Erfan Younesi; Martin Hofmann-Apitius; Natalia Novac
Journal:  Drug Discov Today       Date:  2012-12-29       Impact factor: 7.851

Review 7.  Research Techniques Made Simple: Feature Selection for Biomarker Discovery.

Authors:  Rodrigo Torres; Robert L Judson-Torres
Journal:  J Invest Dermatol       Date:  2019-10       Impact factor: 8.551

8.  Challenges in Biomarker Discovery: Combining Expert Insights with Statistical Analysis of Complex Omics Data.

Authors:  Jason E McDermott; Jing Wang; Hugh Mitchell; Bobbie-Jo Webb-Robertson; Ryan Hafen; John Ramey; Karin D Rodland
Journal:  Expert Opin Med Diagn       Date:  2013-01

9.  Cancer microarray data feature selection using multi-objective binary particle swarm optimization algorithm.

Authors:  Chandra Sekhara Rao Annavarapu; Suresh Dara; Haider Banka
Journal:  EXCLI J       Date:  2016-08-01       Impact factor: 4.068

10.  SVM-RFE: selection and visualization of the most relevant features through non-linear kernels.

Authors:  Hector Sanz; Clarissa Valim; Esteban Vegas; Josep M Oller; Ferran Reverter
Journal:  BMC Bioinformatics       Date:  2018-11-19       Impact factor: 3.169

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