生命物理学理论的雄心壮志

IF 4.6 2区 物理与天体物理 Q1 PHYSICS, MULTIDISCIPLINARY
William Bialek
{"title":"生命物理学理论的雄心壮志","authors":"William Bialek","doi":"10.21468/scipostphyslectnotes.84","DOIUrl":null,"url":null,"abstract":"Theoretical physicists have been fascinated by the phenomena of life for more than a century. As we engage with more realistic descriptions of living systems, however, things get complicated. After reviewing different reactions to this complexity, I explore the optimization of information flow as a potentially general theoretical principle. The primary example is a genetic network guiding development of the fly embryo, but each idea also is illustrated by examples from neural systems. In each case, optimization makes detailed, largely parameter-free predictions that connect quantitatively with experiment.","PeriodicalId":21682,"journal":{"name":"SciPost Physics","volume":"33 1","pages":""},"PeriodicalIF":4.6000,"publicationDate":"2024-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Ambitions for theory in the physics of life\",\"authors\":\"William Bialek\",\"doi\":\"10.21468/scipostphyslectnotes.84\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Theoretical physicists have been fascinated by the phenomena of life for more than a century. As we engage with more realistic descriptions of living systems, however, things get complicated. After reviewing different reactions to this complexity, I explore the optimization of information flow as a potentially general theoretical principle. The primary example is a genetic network guiding development of the fly embryo, but each idea also is illustrated by examples from neural systems. In each case, optimization makes detailed, largely parameter-free predictions that connect quantitatively with experiment.\",\"PeriodicalId\":21682,\"journal\":{\"name\":\"SciPost Physics\",\"volume\":\"33 1\",\"pages\":\"\"},\"PeriodicalIF\":4.6000,\"publicationDate\":\"2024-08-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"SciPost Physics\",\"FirstCategoryId\":\"101\",\"ListUrlMain\":\"https://doi.org/10.21468/scipostphyslectnotes.84\",\"RegionNum\":2,\"RegionCategory\":\"物理与天体物理\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"PHYSICS, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"SciPost Physics","FirstCategoryId":"101","ListUrlMain":"https://doi.org/10.21468/scipostphyslectnotes.84","RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"PHYSICS, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0

摘要

一个多世纪以来,理论物理学家一直对生命现象着迷。然而,当我们对生命系统进行更现实的描述时,情况变得复杂起来。在回顾了对这种复杂性的不同反应之后,我探讨了信息流优化这一潜在的通用理论原则。主要的例子是指导苍蝇胚胎发育的遗传网络,但每个想法也都通过神经系统的例子来说明。在每种情况下,优化都能做出详细的、基本不含参数的预测,并与实验进行定量联系。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Ambitions for theory in the physics of life
Theoretical physicists have been fascinated by the phenomena of life for more than a century. As we engage with more realistic descriptions of living systems, however, things get complicated. After reviewing different reactions to this complexity, I explore the optimization of information flow as a potentially general theoretical principle. The primary example is a genetic network guiding development of the fly embryo, but each idea also is illustrated by examples from neural systems. In each case, optimization makes detailed, largely parameter-free predictions that connect quantitatively with experiment.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
SciPost Physics
SciPost Physics Physics and Astronomy-Physics and Astronomy (all)
CiteScore
8.20
自引率
12.70%
发文量
315
审稿时长
10 weeks
期刊介绍: SciPost Physics publishes breakthrough research articles in the whole field of Physics, covering Experimental, Theoretical and Computational approaches. Specialties covered by this Journal: - Atomic, Molecular and Optical Physics - Experiment - Atomic, Molecular and Optical Physics - Theory - Biophysics - Condensed Matter Physics - Experiment - Condensed Matter Physics - Theory - Condensed Matter Physics - Computational - Fluid Dynamics - Gravitation, Cosmology and Astroparticle Physics - High-Energy Physics - Experiment - High-Energy Physics - Theory - High-Energy Physics - Phenomenology - Mathematical Physics - Nuclear Physics - Experiment - Nuclear Physics - Theory - Quantum Physics - Statistical and Soft Matter Physics.
×
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