Why More Biologists Must Embrace Quantitative Modeling.

IF 2.2 3区 生物学 Q1 ZOOLOGY
Brook G Milligan, Ashley T Rohde
{"title":"Why More Biologists Must Embrace Quantitative Modeling.","authors":"Brook G Milligan, Ashley T Rohde","doi":"10.1093/icb/icae038","DOIUrl":null,"url":null,"abstract":"<p><p>Biology as a field has transformed since the time of its foundation from an organized enterprise cataloging the diversity of the natural world to a quantitatively rigorous science seeking to answer complex questions about the functions of organisms and their interactions with each other and their environments. As the mathematical rigor of biological analyses has improved, quantitative models have been developed to describe multi-mechanistic systems and to test complex hypotheses. However, applications of quantitative models have been uneven across fields, and many biologists lack the foundational training necessary to apply them in their research or to interpret their results to inform biological problem-solving efforts. This gap in scientific training has created a false dichotomy of \"biologists\" and \"modelers\" that only exacerbates the barriers to working biologists seeking additional training in quantitative modeling. Here, we make the argument that all biologists are modelers and are capable of using sophisticated quantitative modeling in their work. We highlight four benefits of conducting biological research within the framework of quantitative models, identify the potential producers and consumers of information produced by such models, and make recommendations for strategies to overcome barriers to their widespread implementation. Improved understanding of quantitative modeling could guide the producers of biological information to better apply biological measurements through analyses that evaluate mechanisms, and allow consumers of biological information to better judge the quality and applications of the information they receive. As our explanations of biological phenomena increase in complexity, so too must we embrace modeling as a foundational skill.</p>","PeriodicalId":54971,"journal":{"name":"Integrative and Comparative Biology","volume":null,"pages":null},"PeriodicalIF":2.2000,"publicationDate":"2024-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Integrative and Comparative Biology","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1093/icb/icae038","RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ZOOLOGY","Score":null,"Total":0}
引用次数: 0

Abstract

Biology as a field has transformed since the time of its foundation from an organized enterprise cataloging the diversity of the natural world to a quantitatively rigorous science seeking to answer complex questions about the functions of organisms and their interactions with each other and their environments. As the mathematical rigor of biological analyses has improved, quantitative models have been developed to describe multi-mechanistic systems and to test complex hypotheses. However, applications of quantitative models have been uneven across fields, and many biologists lack the foundational training necessary to apply them in their research or to interpret their results to inform biological problem-solving efforts. This gap in scientific training has created a false dichotomy of "biologists" and "modelers" that only exacerbates the barriers to working biologists seeking additional training in quantitative modeling. Here, we make the argument that all biologists are modelers and are capable of using sophisticated quantitative modeling in their work. We highlight four benefits of conducting biological research within the framework of quantitative models, identify the potential producers and consumers of information produced by such models, and make recommendations for strategies to overcome barriers to their widespread implementation. Improved understanding of quantitative modeling could guide the producers of biological information to better apply biological measurements through analyses that evaluate mechanisms, and allow consumers of biological information to better judge the quality and applications of the information they receive. As our explanations of biological phenomena increase in complexity, so too must we embrace modeling as a foundational skill.

为什么更多的生物学家必须接受定量建模?
生物学作为一个领域,自其创立以来,已从一个有组织地对自然界的多样性进行编目的事业,转变为一门严谨的定量科学,力求回答有关生物体的功能及其相互之间和与环境之间的相互作用的复杂问题。随着生物分析数学严谨性的提高,定量模型也被开发出来,用于描述多机制系统和检验复杂的假设。然而,定量模型在各个领域的应用并不均衡,许多生物学家缺乏必要的基础培训,无法在研究中应用定量模型,也无法解释定量模型的结果,为解决生物问题提供依据。这种科学培训方面的差距造成了 "生物学家''和 "建模者 "的错误二分法,这只会加剧在职生物学家寻求定量建模额外培训的障碍。在此,我们认为所有生物学家都是建模者,都有能力在工作中使用复杂的定量建模。我们强调了在定量模型框架内开展生物研究的四个好处,确定了这些模型所产生信息的潜在生产者和消费者,并提出了克服广泛应用这些模型的障碍的策略建议。提高对定量模型的理解可以指导生物信息的生产者通过评估机制的分析更好地应用生物测量,并让生物信息的消费者更好地判断他们所接收信息的质量和应用。随着我们对生物现象的解释越来越复杂,我们也必须将建模作为一项基本技能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
CiteScore
4.70
自引率
7.70%
发文量
150
审稿时长
6-12 weeks
期刊介绍: Integrative and Comparative Biology ( ICB ), formerly American Zoologist , is one of the most highly respected and cited journals in the field of biology. The journal''s primary focus is to integrate the varying disciplines in this broad field, while maintaining the highest scientific quality. ICB''s peer-reviewed symposia provide first class syntheses of the top research in a field. ICB also publishes book reviews, reports, and special bulletins.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信