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15 - Essential Patterns, Essential Variables, and Interpretable Biomarkers

from Part IV - Biomarker Discovery via Multistage Signal Enhancement and Identification of Essential Patterns

Published online by Cambridge University Press:  30 May 2024

Darius M. Dziuda
Darius M. Dziuda
Affiliation:
Central Connecticut State University
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Summary

Chapter 15 starts with the identification of essential patterns by analyzing distributions of groups of variables (with similar patterns) among a large number of optimal-size biomarkers generated by parallel feature selection experiments. A similar approach leads to the identification of the essential variables of those essential patterns. As a result, the final multivariate biomarker identified via this method is most likely to represent a real population pattern associated with biological processes underlying changes in the investigated response variable. Furthermore, having the variables of the final biomarker associated with their respective essential patterns facilitates biological interpretation of the biomarker.

Keywords

Essential patternsBiological processesSelf-organizing mapsParsimonious biomarkersFacilitating biological interpretation
Type
Chapter
Information
Multivariate Biomarker Discovery
Data Science Methods for Efficient Analysis of High-Dimensional Biomedical Data
 , pp. 213 - 218
Publisher: Cambridge University Press
Print publication year: 2024

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