AUTHOR=Barajas-Martínez Antonio , Ibarra-Coronado Elizabeth , Sierra-Vargas Martha Patricia , Cruz-Bautista Ivette , Almeda-Valdes Paloma , Aguilar-Salinas Carlos A. , Fossion Ruben , Stephens Christopher R. , Vargas-Domínguez Claudia , Atzatzi-Aguilar Octavio Gamaliel , Debray-García Yazmín , García-Torrentera Rogelio , Bobadilla Karen , Naranjo Meneses María Augusta , Mena Orozco Dulce Abril , Lam-Chung César Ernesto , Martínez Garcés Vania , Lecona Octavio A. , Marín-García Arlex O. , Frank Alejandro , Rivera Ana Leonor TITLE=Physiological Network From Anthropometric and Blood Test Biomarkers JOURNAL=Frontiers in Physiology VOLUME=11 YEAR=2021 URL=https://www.frontiersin.org/journals/physiology/articles/10.3389/fphys.2020.612598 DOI=10.3389/fphys.2020.612598 ISSN=1664-042X ABSTRACT=
Currently, research in physiology focuses on molecular mechanisms underlying the functioning of living organisms. Reductionist strategies are used to decompose systems into their components and to measure changes of physiological variables between experimental conditions. However, how these isolated physiological variables translate into the emergence -and collapse- of biological functions of the organism as a whole is often a less tractable question. To generate a useful representation of physiology as a system, known and unknown interactions between heterogeneous physiological components must be taken into account. In this work we use a Complex Inference Networks approach to build physiological networks from biomarkers. We employ two unrelated databases to generate Spearman correlation matrices of 81 and 54 physiological variables, respectively, including endocrine, mechanic, biochemical, anthropometric, physiological, and cellular variables. From these correlation matrices we generated physiological networks by selecting a