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Front. Mol. Biosci., 10 January 2023
Sec. Metabolomics
Volume 9 - 2022 |

Editorial: Applications of biological networks in biomedicine

www.frontiersin.orgVinicius Maracaja-Coutinho1,2, www.frontiersin.orgAlex Di Genova1,3, www.frontiersin.orgAnne Siegel4 and www.frontiersin.orgMauricio Latorre1,5,6*
  • 1Systemix, Proyecto Anillo ACT210004, Rancagua, Chile
  • 2Advanced Center for Chronic Diseases – ACCDiS, Facultad de Ciencias Químicas y Farmacéuticas, Universidad de Chile, Santiago, Chile
  • 3DiGenoma Lab, Instituto de Ciencias de la Ingeniería, Universidad de O’Higgins, Rancagua, Chile
  • 4Université de Rennes, Inria, CNRS, IRISA, Rennes, France
  • 5Laboratorio de Bioinformática y Expresión Génica, INTA, Universidad de Chile, Santiago, Chile
  • 6Laboratorio de Bioingeniería, Instituto de Ciencias de la Ingeniería, Universidad de O’Higgins, Rancagua, Chile

The field of biomedicine has required the development of Systems Biology studies to understand and analyze phenomena in an integral way. The aim of this special is to exert a real impact on clinical practice and medicine in different areas, such as disease control, early identification of diseases, and development of biomarkers, among others. In this regard, the constant growth of information on a global scale has led to the development of different bioinformatics strategies, which allow the integration of large amounts of data.

Taking this into consideration, the main objective of this Research Topic, entitled “Applications of Biological Networks in Biomedicine”, was to present a series of articles describing the development or use of different platforms on a global scale. Twenty-four different authors managed to deliver valuable information in the fields of metabolomics, multimorbidity, folliculogenesis, and the development of methods to study pathogens clinically resistant to multiple drugs, all of which are relevant biomedicine topics.

First, Ganesan et al. used 1H nuclear magnetic resonance (1H-NMR) to investigate the metabolic effects of single-walled carbon nanotubes (SWCNT) on zebrafish. The analysis of the metabolomics profiling provided a global perspective of the global impact of SWCNT on different metabolic pathways, highlighting those metabolites associated with energy production, amino acids, and nucleotides biosynthesis. These important findings revealed the effects of exposure to organic molecules.

Folliculogenesis is the development of the female germ cell within the somatic cells of the ovary, which matures into a fertilizable egg. Bernabò et al. used a computational biology approach to identify new metabolic sensor molecules that controlled this process and were related to functional endpoints, such as the FSH receptor and steroidogenesis. These results served as a basis for designing innovative diagnostic and treatment methods to preserve female fertility.

Multimorbidity can be defined as the simultaneous presence of two or more chronic diseases. In this context, Dash et al. presented an extensive description of the potential of metabolomics to gain insight into multimorbidity, and also discussed the role of gut microbiota in this pathology. This knowledge led to the development of new treatments related to prebiotics, probiotics, and symbiotic supplementation.

Finally, Tao et al. developed a new test to evaluate certain metabolites that enable antibiotics to kill bacterial pathogens (known as minimum killing concentration, MKC); this interesting approach accelerated the identification of compounds that promote antibiotic-mediated killing efficacy.

As the editor team, we thank and appreciate all authors for their excellent work and commitment to this special issue. We truly believe that our aim was clearly fulfilled because essential findings in Systems Biology were brought together in the context of Biomedicine.

Author contributions

All authors listed have made a substantial, direct, and intellectual contribution to the work and approved it for publication.


This special section was supported by ANID FONDECYT 1190742 (ML), 1211731 (VM) and 1221029 (AD, SUA SA77210017 (AD), ANID BASAL FB210005 (ML), ANID MILENIO ICN2021_044 (ML), ANID ANILLO ACT210004 (ML), and ACT20210044 (ML).

Conflict of interest

The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Keywords: systems biology, biological networks, biomedicine, mathematical modeling, OMICs technics

Citation: Maracaja-Coutinho V, Di Genova A, Siegel A and Latorre M (2023) Editorial: Applications of biological networks in biomedicine. Front. Mol. Biosci. 9:1005183. doi: 10.3389/fmolb.2022.1005183

Received: 28 July 2022; Accepted: 01 September 2022;
Published: 10 January 2023.

Edited and reviewed by:

Wolfram Weckwerth, University of Vienna, Austria

Copyright © 2023 Maracaja-Coutinho, Di Genova, Siegel and Latorre. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Mauricio Latorre,