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Model Misinterpretation within Biology: Phenotypes, Statistics, Networks, and Inference

Models of myriad forms are rapidly becoming central to biology. These range from statistical models that are fundamental to the interpretation of experimental results to ordinary differential equation models that attempt to describe the results in a mechanistic format. Models will be more and more e...

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Detalles Bibliográficos
Autor principal: Kliebenstein, Daniel J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Research Foundation 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3355767/
https://www.ncbi.nlm.nih.gov/pubmed/22645568
http://dx.doi.org/10.3389/fpls.2012.00013
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author Kliebenstein, Daniel J.
author_facet Kliebenstein, Daniel J.
author_sort Kliebenstein, Daniel J.
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description Models of myriad forms are rapidly becoming central to biology. These range from statistical models that are fundamental to the interpretation of experimental results to ordinary differential equation models that attempt to describe the results in a mechanistic format. Models will be more and more essential to biologists but this growing importance requires all model users to become more sophisticated about what is in a model and how that limits the usability of the model. This review attempts to relay the potential pitfalls that can lie within a model.
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spelling pubmed-33557672012-05-29 Model Misinterpretation within Biology: Phenotypes, Statistics, Networks, and Inference Kliebenstein, Daniel J. Front Plant Sci Plant Science Models of myriad forms are rapidly becoming central to biology. These range from statistical models that are fundamental to the interpretation of experimental results to ordinary differential equation models that attempt to describe the results in a mechanistic format. Models will be more and more essential to biologists but this growing importance requires all model users to become more sophisticated about what is in a model and how that limits the usability of the model. This review attempts to relay the potential pitfalls that can lie within a model. Frontiers Research Foundation 2012-01-31 /pmc/articles/PMC3355767/ /pubmed/22645568 http://dx.doi.org/10.3389/fpls.2012.00013 Text en Copyright © 2012 Kliebenstein. http://www.frontiersin.org/licenseagreement This is an open-access article distributed under the terms of the Creative Commons Attribution Non Commercial License, which permits non-commercial use, distribution, and reproduction in other forums, provided the original authors and source are credited.
spellingShingle Plant Science
Kliebenstein, Daniel J.
Model Misinterpretation within Biology: Phenotypes, Statistics, Networks, and Inference
title Model Misinterpretation within Biology: Phenotypes, Statistics, Networks, and Inference
title_full Model Misinterpretation within Biology: Phenotypes, Statistics, Networks, and Inference
title_fullStr Model Misinterpretation within Biology: Phenotypes, Statistics, Networks, and Inference
title_full_unstemmed Model Misinterpretation within Biology: Phenotypes, Statistics, Networks, and Inference
title_short Model Misinterpretation within Biology: Phenotypes, Statistics, Networks, and Inference
title_sort model misinterpretation within biology: phenotypes, statistics, networks, and inference
topic Plant Science
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3355767/
https://www.ncbi.nlm.nih.gov/pubmed/22645568
http://dx.doi.org/10.3389/fpls.2012.00013
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