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State-Transition Diagrams for Biologists

It is clearly in the tradition of biologists to conceptualize the dynamical evolution of biological systems in terms of state-transitions of biological objects. This paper is mainly concerned with (but obviously not limited too) the immunological branch of biology and shows how the adoption of UML (...

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Autores principales: Bersini, Hugues, Klatzmann, David, Six, Adrien, Thomas-Vaslin, Véronique
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3402529/
https://www.ncbi.nlm.nih.gov/pubmed/22844438
http://dx.doi.org/10.1371/journal.pone.0041165
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author Bersini, Hugues
Klatzmann, David
Six, Adrien
Thomas-Vaslin, Véronique
author_facet Bersini, Hugues
Klatzmann, David
Six, Adrien
Thomas-Vaslin, Véronique
author_sort Bersini, Hugues
collection PubMed
description It is clearly in the tradition of biologists to conceptualize the dynamical evolution of biological systems in terms of state-transitions of biological objects. This paper is mainly concerned with (but obviously not limited too) the immunological branch of biology and shows how the adoption of UML (Unified Modeling Language) state-transition diagrams can ease the modeling, the understanding, the coding, the manipulation or the documentation of population-based immune software model generally defined as a set of ordinary differential equations (ODE), describing the evolution in time of populations of various biological objects. Moreover, that same UML adoption naturally entails a far from negligible representational economy since one graphical item of the diagram might have to be repeated in various places of the mathematical model. First, the main graphical elements of the UML state-transition diagram and how they can be mapped onto a corresponding ODE mathematical model are presented. Then, two already published immune models of thymocyte behavior and time evolution in the thymus, the first one originally conceived as an ODE population-based model whereas the second one as an agent-based one, are refactored and expressed in a state-transition form so as to make them much easier to understand and their respective code easier to access, to modify and run. As an illustrative proof, for any immunologist, it should be possible to understand faithfully enough what the two software models are supposed to reproduce and how they execute with no need to plunge into the Java or Fortran lines.
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spelling pubmed-34025292012-07-27 State-Transition Diagrams for Biologists Bersini, Hugues Klatzmann, David Six, Adrien Thomas-Vaslin, Véronique PLoS One Research Article It is clearly in the tradition of biologists to conceptualize the dynamical evolution of biological systems in terms of state-transitions of biological objects. This paper is mainly concerned with (but obviously not limited too) the immunological branch of biology and shows how the adoption of UML (Unified Modeling Language) state-transition diagrams can ease the modeling, the understanding, the coding, the manipulation or the documentation of population-based immune software model generally defined as a set of ordinary differential equations (ODE), describing the evolution in time of populations of various biological objects. Moreover, that same UML adoption naturally entails a far from negligible representational economy since one graphical item of the diagram might have to be repeated in various places of the mathematical model. First, the main graphical elements of the UML state-transition diagram and how they can be mapped onto a corresponding ODE mathematical model are presented. Then, two already published immune models of thymocyte behavior and time evolution in the thymus, the first one originally conceived as an ODE population-based model whereas the second one as an agent-based one, are refactored and expressed in a state-transition form so as to make them much easier to understand and their respective code easier to access, to modify and run. As an illustrative proof, for any immunologist, it should be possible to understand faithfully enough what the two software models are supposed to reproduce and how they execute with no need to plunge into the Java or Fortran lines. Public Library of Science 2012-07-23 /pmc/articles/PMC3402529/ /pubmed/22844438 http://dx.doi.org/10.1371/journal.pone.0041165 Text en Bersini et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Bersini, Hugues
Klatzmann, David
Six, Adrien
Thomas-Vaslin, Véronique
State-Transition Diagrams for Biologists
title State-Transition Diagrams for Biologists
title_full State-Transition Diagrams for Biologists
title_fullStr State-Transition Diagrams for Biologists
title_full_unstemmed State-Transition Diagrams for Biologists
title_short State-Transition Diagrams for Biologists
title_sort state-transition diagrams for biologists
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3402529/
https://www.ncbi.nlm.nih.gov/pubmed/22844438
http://dx.doi.org/10.1371/journal.pone.0041165
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