Bioimaging and-the future of whole-organismal developmental physiology.

IF 2.1 3区 生物学 Q4 BIOCHEMISTRY & MOLECULAR BIOLOGY Comparative Biochemistry and Physiology A-Molecular & Integrative Physiology Pub Date : 2024-11-22 DOI:10.1016/j.cbpa.2024.111783
Oliver Tills, Ziad Ibbini, John I Spicer
{"title":"Bioimaging and-the future of whole-organismal developmental physiology.","authors":"Oliver Tills, Ziad Ibbini, John I Spicer","doi":"10.1016/j.cbpa.2024.111783","DOIUrl":null,"url":null,"abstract":"<p><p>While omics has transformed the study of biology, concomitant advances made at the level of the whole organism, i.e. the phenome, have arguably not kept pace with lower levels of biological organisation. In this personal commentary we evaluate the importance of imaging as a means of measuring whole organismal developmental physiology. Image acquisition, while an important process itself, has become secondary to image analysis as a bottleneck to the use of imaging in research. Here, we explore the significant potential for increasingly sophisticated approaches to image analysis, including deep learning, to advance our understanding of how developing animals grow and function. Furthermore, unlike many species-specific methodologies, tools and technologies, we explore how computer vision has the potential to be transferable between species, life stages, experiments and even taxa in which embryonic development can be imaged. We identify what we consider are six of the key challenges and opportunities in the application of computer vision to developmental physiology carried out in our lab, and more generally. We reflect on the tangibility of transferrable computer vision models capable of measuring the integrative physiology of a broad range of developing organisms, and thereby driving the adoption of phenomics for developmental physiology. We are at an exciting time of witnessing the move from computer vision as a replacement for manual observation, or manual image analysis, to it enabling a fundamentally more powerful approach to exploring and understanding the complex biology of developing organisms, the quantification of which has long posed a challenge to researchers.</p>","PeriodicalId":55237,"journal":{"name":"Comparative Biochemistry and Physiology A-Molecular & Integrative Physiology","volume":" ","pages":"111783"},"PeriodicalIF":2.1000,"publicationDate":"2024-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Comparative Biochemistry and Physiology A-Molecular & Integrative Physiology","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1016/j.cbpa.2024.111783","RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}
引用次数: 0

Abstract

While omics has transformed the study of biology, concomitant advances made at the level of the whole organism, i.e. the phenome, have arguably not kept pace with lower levels of biological organisation. In this personal commentary we evaluate the importance of imaging as a means of measuring whole organismal developmental physiology. Image acquisition, while an important process itself, has become secondary to image analysis as a bottleneck to the use of imaging in research. Here, we explore the significant potential for increasingly sophisticated approaches to image analysis, including deep learning, to advance our understanding of how developing animals grow and function. Furthermore, unlike many species-specific methodologies, tools and technologies, we explore how computer vision has the potential to be transferable between species, life stages, experiments and even taxa in which embryonic development can be imaged. We identify what we consider are six of the key challenges and opportunities in the application of computer vision to developmental physiology carried out in our lab, and more generally. We reflect on the tangibility of transferrable computer vision models capable of measuring the integrative physiology of a broad range of developing organisms, and thereby driving the adoption of phenomics for developmental physiology. We are at an exciting time of witnessing the move from computer vision as a replacement for manual observation, or manual image analysis, to it enabling a fundamentally more powerful approach to exploring and understanding the complex biology of developing organisms, the quantification of which has long posed a challenge to researchers.

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
生物成像和整个有机体发育生理学的未来。
虽然全息技术改变了生物学研究,但在整个生物体(即表型组)层面上取得的相应进展却没有跟上较低层次生物组织的步伐。在这篇个人评论中,我们评估了成像作为测量整个生物体发育生理学的一种手段的重要性。图像获取本身是一个重要的过程,但图像分析已成为研究中使用图像的瓶颈。在这里,我们将探讨日益复杂的图像分析方法(包括深度学习)的巨大潜力,以促进我们对发育中动物的生长和功能的了解。此外,与许多针对特定物种的方法、工具和技术不同,我们探讨了计算机视觉如何具有在不同物种、生命阶段、实验,甚至可以对胚胎发育进行成像的类群之间进行移植的潜力。我们确定了我们认为在我们实验室以及更广泛的范围内将计算机视觉应用于发育生理学的六个关键挑战和机遇。我们思考了计算机视觉模型的可移植性,该模型能够测量各种发育中生物的综合生理学,从而推动表型组学在发育生理学中的应用。我们正处于一个激动人心的时刻,见证着计算机视觉从替代人工观察或人工图像分析,发展到能够从根本上以更强大的方法探索和理解发育中生物体的复杂生物学特性,而量化这些特性长期以来一直是研究人员面临的挑战。
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 去求助
来源期刊
CiteScore
5.00
自引率
4.30%
发文量
155
审稿时长
3 months
期刊介绍: Part A: Molecular & Integrative Physiology of Comparative Biochemistry and Physiology. This journal covers molecular, cellular, integrative, and ecological physiology. Topics include bioenergetics, circulation, development, excretion, ion regulation, endocrinology, neurobiology, nutrition, respiration, and thermal biology. Study on regulatory mechanisms at any level of organization such as signal transduction and cellular interaction and control of behavior are also published.
期刊最新文献
Bioimaging and-the future of whole-organismal developmental physiology. Kinetic comparisons of jaw opening, jaw closing and locomotor muscles. Short communication: Can Vitamin D be supplied from the large intestine? Small heat shock proteins as relevant biomarkers for anthropogenic stressors in earthworms. Editorial Board
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1