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基于微阵列实验的生物标志物检测的有监督方法。

Supervised Methods for Biomarker Detection from Microarray Experiments.

机构信息

Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland.

BioMediTech Institute, Tampere University, Tampere, Finland.

出版信息

Methods Mol Biol. 2022;2401:101-120. doi: 10.1007/978-1-0716-1839-4_8.

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.

摘要

生物标志物是生物系统状态的有价值的指标。微阵列技术已被广泛用于识别生物标志物,并构建用于疾病预后、药物敏感性和毒性评估的计算预测模型。激活生物标志物可用于了解潜在的信号级联、作用机制和生物串扰。从微阵列数据中检测生物标志物需要从生物学和计算两个角度考虑几个因素。在本章中,我们描述了在生物标志物发现和预测建模中使用的主要方法,并解决了一些相关的挑战。此外,我们讨论了生物标志物的验证,并深入探讨了用于生物标志物检测的多组学策略。

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