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The Spectrum of Mechanism-Oriented Models and Methods for Explanations of Biological Phenomena
Developing and improving mechanism-oriented computational models to better explain biological phenomena is a dynamic and expanding frontier. As the complexity of targeted phenomena has increased, so too has the diversity in methods and terminologies, often at the expense of clarity, which can make r...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8277120/ https://www.ncbi.nlm.nih.gov/pubmed/34262852 http://dx.doi.org/10.3390/pr6050056 |
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author | Hunt, C. Anthony Erdemir, Ahmet Lytton, William W. Gabhann, Feilim Mac Sander, Edward A. Transtrum, Mark K. Mulugeta, Lealem |
author_facet | Hunt, C. Anthony Erdemir, Ahmet Lytton, William W. Gabhann, Feilim Mac Sander, Edward A. Transtrum, Mark K. Mulugeta, Lealem |
author_sort | Hunt, C. Anthony |
collection | PubMed |
description | Developing and improving mechanism-oriented computational models to better explain biological phenomena is a dynamic and expanding frontier. As the complexity of targeted phenomena has increased, so too has the diversity in methods and terminologies, often at the expense of clarity, which can make reproduction challenging, even problematic. To encourage improved semantic and methodological clarity, we describe the spectrum of Mechanism-oriented Models being used to develop explanations of biological phenomena. We cluster explanations of phenomena into three broad groups. We then expand them into seven workflow-related model types having distinguishable features. We name each type and illustrate with examples drawn from the literature. These model types may contribute to the foundation of an ontology of mechanism-based biomedical simulation research. We show that the different model types manifest and exert their scientific usefulness by enhancing and extending different forms and degrees of explanation. The process starts with knowledge about the phenomenon and continues with explanatory and mathematical descriptions. Those descriptions are transformed into software and used to perform experimental explorations by running and examining simulation output. The credibility of inferences is thus linked to having easy access to the scientific and technical provenance from each workflow stage. |
format | Online Article Text |
id | pubmed-8277120 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
record_format | MEDLINE/PubMed |
spelling | pubmed-82771202021-07-13 The Spectrum of Mechanism-Oriented Models and Methods for Explanations of Biological Phenomena Hunt, C. Anthony Erdemir, Ahmet Lytton, William W. Gabhann, Feilim Mac Sander, Edward A. Transtrum, Mark K. Mulugeta, Lealem Processes (Basel) Article Developing and improving mechanism-oriented computational models to better explain biological phenomena is a dynamic and expanding frontier. As the complexity of targeted phenomena has increased, so too has the diversity in methods and terminologies, often at the expense of clarity, which can make reproduction challenging, even problematic. To encourage improved semantic and methodological clarity, we describe the spectrum of Mechanism-oriented Models being used to develop explanations of biological phenomena. We cluster explanations of phenomena into three broad groups. We then expand them into seven workflow-related model types having distinguishable features. We name each type and illustrate with examples drawn from the literature. These model types may contribute to the foundation of an ontology of mechanism-based biomedical simulation research. We show that the different model types manifest and exert their scientific usefulness by enhancing and extending different forms and degrees of explanation. The process starts with knowledge about the phenomenon and continues with explanatory and mathematical descriptions. Those descriptions are transformed into software and used to perform experimental explorations by running and examining simulation output. The credibility of inferences is thus linked to having easy access to the scientific and technical provenance from each workflow stage. 2018-05-14 2018-05 /pmc/articles/PMC8277120/ /pubmed/34262852 http://dx.doi.org/10.3390/pr6050056 Text en https://creativecommons.org/licenses/by/4.0/This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ). |
spellingShingle | Article Hunt, C. Anthony Erdemir, Ahmet Lytton, William W. Gabhann, Feilim Mac Sander, Edward A. Transtrum, Mark K. Mulugeta, Lealem The Spectrum of Mechanism-Oriented Models and Methods for Explanations of Biological Phenomena |
title | The Spectrum of Mechanism-Oriented Models and Methods for Explanations of Biological Phenomena |
title_full | The Spectrum of Mechanism-Oriented Models and Methods for Explanations of Biological Phenomena |
title_fullStr | The Spectrum of Mechanism-Oriented Models and Methods for Explanations of Biological Phenomena |
title_full_unstemmed | The Spectrum of Mechanism-Oriented Models and Methods for Explanations of Biological Phenomena |
title_short | The Spectrum of Mechanism-Oriented Models and Methods for Explanations of Biological Phenomena |
title_sort | spectrum of mechanism-oriented models and methods for explanations of biological phenomena |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8277120/ https://www.ncbi.nlm.nih.gov/pubmed/34262852 http://dx.doi.org/10.3390/pr6050056 |
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