Separating Biological Variance from Noise by Applying Expectation-Maximization Algorithm to Modified General Linear Model

The general linear model (GLM) has been widely used in research, where the error term has been treated as noise. However, compelling evidence suggests that in biological systems, the target variables may possess their innate variances. A modified GLM was proposed to explicitly model biological varia...

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Bibliographic Details

Published in:	Journal of computational biology Vol. 32; no. 12; p. 1121
Main Author:	Lee, Tien-Wen
Format:	Journal Article
Language:	English
Published:	United States 05.09.2025
Subjects:	Algorithms Humans Linear Models Models, Biological Signal-To-Noise Ratio expectation–maximization algorithm design matrix global optimum general linear model local optimum
ISSN:	1557-8666, 1557-8666
Online Access:	Get more information
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