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“Gestaltomics”: Systems Biology Schemes for the Study of Neuropsychiatric Diseases
The integration of different sources of biological information about what defines a behavioral phenotype is difficult to unify in an entity that reflects the arithmetic sum of its individual parts. In this sense, the challenge of Systems Biology for understanding the “psychiatric phenotype” is to pr...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2017
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5422874/ https://www.ncbi.nlm.nih.gov/pubmed/28536537 http://dx.doi.org/10.3389/fphys.2017.00286 |
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author | Gutierrez Najera, Nora A. Resendis-Antonio, Osbaldo Nicolini, Humberto |
author_facet | Gutierrez Najera, Nora A. Resendis-Antonio, Osbaldo Nicolini, Humberto |
author_sort | Gutierrez Najera, Nora A. |
collection | PubMed |
description | The integration of different sources of biological information about what defines a behavioral phenotype is difficult to unify in an entity that reflects the arithmetic sum of its individual parts. In this sense, the challenge of Systems Biology for understanding the “psychiatric phenotype” is to provide an improved vision of the shape of the phenotype as it is visualized by “Gestalt” psychology, whose fundamental axiom is that the observed phenotype (behavior or mental disorder) will be the result of the integrative composition of every part. Therefore, we propose the term “Gestaltomics” as a term from Systems Biology to integrate data coming from different sources of information (such as the genome, transcriptome, proteome, epigenome, metabolome, phenome, and microbiome). In addition to this biological complexity, the mind is integrated through multiple brain functions that receive and process complex information through channels and perception networks (i.e., sight, ear, smell, memory, and attention) that in turn are programmed by genes and influenced by environmental processes (epigenetic). Today, the approach of medical research in human diseases is to isolate one disease for study; however, the presence of an additional disease (co-morbidity) or more than one disease (multimorbidity) adds complexity to the study of these conditions. This review will present the challenge of integrating psychiatric disorders at different levels of information (Gestaltomics). The implications of increasing the level of complexity, for example, studying the co-morbidity with another disease such as cancer, will also be discussed. |
format | Online Article Text |
id | pubmed-5422874 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-54228742017-05-23 “Gestaltomics”: Systems Biology Schemes for the Study of Neuropsychiatric Diseases Gutierrez Najera, Nora A. Resendis-Antonio, Osbaldo Nicolini, Humberto Front Physiol Physiology The integration of different sources of biological information about what defines a behavioral phenotype is difficult to unify in an entity that reflects the arithmetic sum of its individual parts. In this sense, the challenge of Systems Biology for understanding the “psychiatric phenotype” is to provide an improved vision of the shape of the phenotype as it is visualized by “Gestalt” psychology, whose fundamental axiom is that the observed phenotype (behavior or mental disorder) will be the result of the integrative composition of every part. Therefore, we propose the term “Gestaltomics” as a term from Systems Biology to integrate data coming from different sources of information (such as the genome, transcriptome, proteome, epigenome, metabolome, phenome, and microbiome). In addition to this biological complexity, the mind is integrated through multiple brain functions that receive and process complex information through channels and perception networks (i.e., sight, ear, smell, memory, and attention) that in turn are programmed by genes and influenced by environmental processes (epigenetic). Today, the approach of medical research in human diseases is to isolate one disease for study; however, the presence of an additional disease (co-morbidity) or more than one disease (multimorbidity) adds complexity to the study of these conditions. This review will present the challenge of integrating psychiatric disorders at different levels of information (Gestaltomics). The implications of increasing the level of complexity, for example, studying the co-morbidity with another disease such as cancer, will also be discussed. Frontiers Media S.A. 2017-05-09 /pmc/articles/PMC5422874/ /pubmed/28536537 http://dx.doi.org/10.3389/fphys.2017.00286 Text en Copyright © 2017 Gutierrez Najera, Resendis-Antonio and Nicolini. http://creativecommons.org/licenses/by/4.0/ 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) or licensor 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. |
spellingShingle | Physiology Gutierrez Najera, Nora A. Resendis-Antonio, Osbaldo Nicolini, Humberto “Gestaltomics”: Systems Biology Schemes for the Study of Neuropsychiatric Diseases |
title | “Gestaltomics”: Systems Biology Schemes for the Study of Neuropsychiatric Diseases |
title_full | “Gestaltomics”: Systems Biology Schemes for the Study of Neuropsychiatric Diseases |
title_fullStr | “Gestaltomics”: Systems Biology Schemes for the Study of Neuropsychiatric Diseases |
title_full_unstemmed | “Gestaltomics”: Systems Biology Schemes for the Study of Neuropsychiatric Diseases |
title_short | “Gestaltomics”: Systems Biology Schemes for the Study of Neuropsychiatric Diseases |
title_sort | “gestaltomics”: systems biology schemes for the study of neuropsychiatric diseases |
topic | Physiology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5422874/ https://www.ncbi.nlm.nih.gov/pubmed/28536537 http://dx.doi.org/10.3389/fphys.2017.00286 |
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