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SEM: Structural Equation Modeling in Molecular Biology

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Abstract

Structural equation modeling (SEM) is a second-generation multivariate method to estimate the causal interactions in a set of variables and includes, as special cases, several statistical methods (regression analysis, path analysis, and confirmatory factor analysis). This review focuses on all of the main SEM models and various methods used to optimize the model parameters. Representative examples are discussed to illustrate SEM application in molecular biology, including modeling of biochemical processes, relationships between genetic markers and diseases, and interactions within gene networks.

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Abbreviations

SEM:

structural equation modeling

LISREL:

linear structural relations

RMSEA:

root mean square error of approximation

SRMR:

standardized root mean square residual

SNP:

single nucleotide polymorphism

MAPK:

mitogenactivated protein kinase

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Authors and Affiliations

  1. Peter the Great St. Petersburg Polytechnic University, St. Petersburg, 195251, Russia

    A. A. Igolkina & M. G. Samsonova

Authors
  1. A. A. Igolkina
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  2. M. G. Samsonova
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Correspondence to A. A. Igolkina.

Additional information

Original Russian Text © A.A. Igolkina, M.G. Samsonova, 2018, published in Biofizika, 2018, Vol. 63, No. 2, pp. 213–224.

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Igolkina, A.A., Samsonova, M.G. SEM: Structural Equation Modeling in Molecular Biology. BIOPHYSICS 63, 139–148 (2018). https://doi.org/10.1134/S0006350918020100

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