Ten simple rules for principled simulation modelling
[...]the term “model” is often defined in terms of its aim. Models of evolutionary processes are similar—they often focus on mechanistic insight, as scientific researchers are often most interested in “why” questions, and many branches of evolutionary theory were also developed with real-world, prec...
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Veröffentlicht in: | PLoS computational biology 2022-03, Vol.18 (3), p.e1009917-e1009917 |
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description | [...]the term “model” is often defined in terms of its aim. Models of evolutionary processes are similar—they often focus on mechanistic insight, as scientific researchers are often most interested in “why” questions, and many branches of evolutionary theory were also developed with real-world, precise prediction in mind (see, e.g., [8]; see also [9] and citations therein for a discussion of prediction in evolution). Assuming that some mechanistic insight is the aim, based on knowledge of the system and precise formulation of the research question, a good strategy is to identify putative interactions or mechanisms that could underlie the behaviour or phenomenon under investigation and model those mechanisms. Alongside the mathematical and technical details of each part of the model, careful consideration should be given to the order in which these parts or processes are executed and what effect that ordering (or scheduling) has on the output. |
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This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2022 Fogarty et al 2022 Fogarty et al</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c633t-a443c7719d779da02398f661ebba2530f5f45d1681387084ea96e76b333098a73</citedby><cites>FETCH-LOGICAL-c633t-a443c7719d779da02398f661ebba2530f5f45d1681387084ea96e76b333098a73</cites><orcidid>0000-0002-1031-3786 ; 0000-0002-3579-9735 ; 0000-0002-9386-6414 ; 0000-0003-3766-6597 ; 0000-0002-2846-3790</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8970361/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8970361/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,864,885,2102,2928,23866,27924,27925,53791,53793,79600,79601</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/35358175$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Schwartz, Russell</contributor><creatorcontrib>Fogarty, Laurel</creatorcontrib><creatorcontrib>Ammar, Madeleine</creatorcontrib><creatorcontrib>Holding, Thomas</creatorcontrib><creatorcontrib>Powell, Adam</creatorcontrib><creatorcontrib>Kandler, Anne</creatorcontrib><title>Ten simple rules for principled simulation modelling</title><title>PLoS computational biology</title><addtitle>PLoS Comput Biol</addtitle><description>[...]the term “model” is often defined in terms of its aim. Models of evolutionary processes are similar—they often focus on mechanistic insight, as scientific researchers are often most interested in “why” questions, and many branches of evolutionary theory were also developed with real-world, precise prediction in mind (see, e.g., [8]; see also [9] and citations therein for a discussion of prediction in evolution). Assuming that some mechanistic insight is the aim, based on knowledge of the system and precise formulation of the research question, a good strategy is to identify putative interactions or mechanisms that could underlie the behaviour or phenomenon under investigation and model those mechanisms. Alongside the mathematical and technical details of each part of the model, careful consideration should be given to the order in which these parts or processes are executed and what effect that ordering (or scheduling) has on the output.</description><subject>Algorithms</subject><subject>Computer and Information Sciences</subject><subject>Computer Simulation</subject><subject>Design</subject><subject>Earth Sciences</subject><subject>Education</subject><subject>Engineering and Technology</subject><subject>Evolution</subject><subject>Evolutionary biology</subject><subject>Mathematical models</subject><subject>Physical Sciences</subject><subject>Questions</subject><subject>Research and Analysis Methods</subject><subject>Simulation</subject><subject>Simulation methods</subject><subject>Social Sciences</subject><subject>Solar 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subjects | Algorithms Computer and Information Sciences Computer Simulation Design Earth Sciences Education Engineering and Technology Evolution Evolutionary biology Mathematical models Physical Sciences Questions Research and Analysis Methods Simulation Simulation methods Social Sciences Solar system |
title | Ten simple rules for principled simulation modelling |
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