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Lessons and perspectives for applications of stochastic models in biological and cancer research

The effects of randomness, an unavoidable feature of intracellular environments, are observed at higher hierarchical levels of living matter organization, such as cells, tissues, and organisms. Additionally, the many compounds interacting as a well-orchestrated network of reactions increase the diff...

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Autores principales: Sabino, Alan U, Vasconcelos, Miguel FS, Sittoni, Misaki Yamada, Lautenschlager, Willian W, Queiroga, Alexandre S, Morais, Mauro CC, Ramos, Alexandre F
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6131223/
https://www.ncbi.nlm.nih.gov/pubmed/30281699
http://dx.doi.org/10.6061/clinics/2018/e536s
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author Sabino, Alan U
Vasconcelos, Miguel FS
Sittoni, Misaki Yamada
Lautenschlager, Willian W
Queiroga, Alexandre S
Morais, Mauro CC
Ramos, Alexandre F
author_facet Sabino, Alan U
Vasconcelos, Miguel FS
Sittoni, Misaki Yamada
Lautenschlager, Willian W
Queiroga, Alexandre S
Morais, Mauro CC
Ramos, Alexandre F
author_sort Sabino, Alan U
collection PubMed
description The effects of randomness, an unavoidable feature of intracellular environments, are observed at higher hierarchical levels of living matter organization, such as cells, tissues, and organisms. Additionally, the many compounds interacting as a well-orchestrated network of reactions increase the difficulties of assessing these systems using only experiments. This limitation indicates that elucidation of the dynamics of biological systems is a complex task that will benefit from the establishment of principles to help describe, categorize, and predict the behavior of these systems. The theoretical machinery already available, or ones to be discovered to help solve biological problems, might play an important role in these processes. Here, we demonstrate the application of theoretical tools by discussing some biological problems that we have approached mathematically: fluctuations in gene expression and cell proliferation in the context of loss of contact inhibition. We discuss the methods that have been employed to provide the reader with a biologically motivated phenomenological perspective of the use of theoretical methods. Finally, we end this review with a discussion of new research perspectives motivated by our results.
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spelling pubmed-61312232018-09-12 Lessons and perspectives for applications of stochastic models in biological and cancer research Sabino, Alan U Vasconcelos, Miguel FS Sittoni, Misaki Yamada Lautenschlager, Willian W Queiroga, Alexandre S Morais, Mauro CC Ramos, Alexandre F Clinics (Sao Paulo) Review Article The effects of randomness, an unavoidable feature of intracellular environments, are observed at higher hierarchical levels of living matter organization, such as cells, tissues, and organisms. Additionally, the many compounds interacting as a well-orchestrated network of reactions increase the difficulties of assessing these systems using only experiments. This limitation indicates that elucidation of the dynamics of biological systems is a complex task that will benefit from the establishment of principles to help describe, categorize, and predict the behavior of these systems. The theoretical machinery already available, or ones to be discovered to help solve biological problems, might play an important role in these processes. Here, we demonstrate the application of theoretical tools by discussing some biological problems that we have approached mathematically: fluctuations in gene expression and cell proliferation in the context of loss of contact inhibition. We discuss the methods that have been employed to provide the reader with a biologically motivated phenomenological perspective of the use of theoretical methods. Finally, we end this review with a discussion of new research perspectives motivated by our results. Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo 2018-09-11 2018 /pmc/articles/PMC6131223/ /pubmed/30281699 http://dx.doi.org/10.6061/clinics/2018/e536s Text en Copyright © 2018 CLINICS http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium or format, provided the original work is properly cited.
spellingShingle Review Article
Sabino, Alan U
Vasconcelos, Miguel FS
Sittoni, Misaki Yamada
Lautenschlager, Willian W
Queiroga, Alexandre S
Morais, Mauro CC
Ramos, Alexandre F
Lessons and perspectives for applications of stochastic models in biological and cancer research
title Lessons and perspectives for applications of stochastic models in biological and cancer research
title_full Lessons and perspectives for applications of stochastic models in biological and cancer research
title_fullStr Lessons and perspectives for applications of stochastic models in biological and cancer research
title_full_unstemmed Lessons and perspectives for applications of stochastic models in biological and cancer research
title_short Lessons and perspectives for applications of stochastic models in biological and cancer research
title_sort lessons and perspectives for applications of stochastic models in biological and cancer research
topic Review Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6131223/
https://www.ncbi.nlm.nih.gov/pubmed/30281699
http://dx.doi.org/10.6061/clinics/2018/e536s
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