• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

全细胞建模的数据整合策略。

Data integration strategies for whole-cell modeling.

作者信息

Tummler Katja, Klipp Edda

机构信息

Humboldt-Universität zu Berlin, Faculty of Life Sciences, Institute of Biology, Theoretical Biophysics,, Invalidenstr. 42, 10115 Berlin, Germany.

出版信息

FEMS Yeast Res. 2024 Jan 9;24. doi: 10.1093/femsyr/foae011.

DOI:10.1093/femsyr/foae011
PMID:38544322
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11042497/
Abstract

Data makes the world go round-and high quality data is a prerequisite for precise models, especially for whole-cell models (WCM). Data for WCM must be reusable, contain information about the exact experimental background, and should-in its entirety-cover all relevant processes in the cell. Here, we review basic requirements to data for WCM and strategies how to combine them. As a species-specific resource, we introduce the Yeast Cell Model Data Base (YCMDB) to illustrate requirements and solutions. We discuss recent standards for data as well as for computational models including the modeling process as data to be reported. We outline strategies for constructions of WCM despite their inherent complexity.

摘要

数据推动世界运转,而高质量数据是精确模型的先决条件,尤其是对于全细胞模型(WCM)而言。WCM的数据必须可重复使用,包含有关确切实验背景的信息,并且应整体涵盖细胞中的所有相关过程。在此,我们回顾了WCM数据的基本要求以及将它们结合起来的策略。作为一种物种特异性资源,我们引入酵母细胞模型数据库(YCMDB)来说明要求和解决方案。我们讨论了数据以及计算模型的最新标准,包括作为要报告的数据的建模过程。尽管WCM具有内在复杂性,我们仍概述了构建WCM的策略。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b8b5/11042497/378f18d7ff28/foae011fig5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b8b5/11042497/36dc48c3bc96/foae011fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b8b5/11042497/fbd0fd9aa0b9/foae011fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b8b5/11042497/ca69b99c476c/foae011fig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b8b5/11042497/2487c91af2d7/foae011fig4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b8b5/11042497/378f18d7ff28/foae011fig5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b8b5/11042497/36dc48c3bc96/foae011fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b8b5/11042497/fbd0fd9aa0b9/foae011fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b8b5/11042497/ca69b99c476c/foae011fig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b8b5/11042497/2487c91af2d7/foae011fig4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b8b5/11042497/378f18d7ff28/foae011fig5.jpg

相似文献

1
Data integration strategies for whole-cell modeling.全细胞建模的数据整合策略。
FEMS Yeast Res. 2024 Jan 9;24. doi: 10.1093/femsyr/foae011.
2
Standards, tools, and databases for the analysis of yeast 'omics data.用于分析酵母组学数据的标准、工具和数据库。
Methods Mol Biol. 2011;759:345-65. doi: 10.1007/978-1-61779-173-4_20.
3
Data and model integration using JWS Online.使用JWS在线工具进行数据与模型整合。
In Silico Biol. 2007;7(2 Suppl):S27-35.
4
The bacterial interlocked process ONtology (BiPON): a systemic multi-scale unified representation of biological processes in prokaryotes.细菌连锁过程本体论(BiPON):原核生物中生物过程的系统多尺度统一表示。
J Biomed Semantics. 2017 Nov 23;8(1):53. doi: 10.1186/s13326-017-0165-6.
5
AVID: an integrative framework for discovering functional relationships among proteins.AVID:一个用于发现蛋白质间功能关系的综合框架。
BMC Bioinformatics. 2005 Jun 1;6:136. doi: 10.1186/1471-2105-6-136.
6
Towards cooperative frameworks for modeling and integrating biological processes knowledge.迈向用于建模和整合生物过程知识的协作框架。
IEEE Trans Nanobioscience. 2004 Sep;3(3):164-71. doi: 10.1109/tnb.2004.833685.
7
An overview of bioinformatics methods for modeling biological pathways in yeast.用于酵母生物途径建模的生物信息学方法综述。
Brief Funct Genomics. 2016 Mar;15(2):95-108. doi: 10.1093/bfgp/elv040. Epub 2015 Oct 17.
8
Effects of functional bias on supervised learning of a gene network model.功能偏差对基因网络模型监督学习的影响。
Methods Mol Biol. 2009;541:463-75. doi: 10.1007/978-1-59745-243-4_20.
9
Is newer better?--evaluating the effects of data curation on integrated analyses in Saccharomyces cerevisiae.更新更好吗?——评估 Saccharomyces cerevisiae 中数据管理对整合分析的影响。
Integr Biol (Camb). 2012 Jul;4(7):715-27. doi: 10.1039/c2ib00123c. Epub 2012 Apr 23.
10
Modeling yeast osmoadaptation at different levels of resolution.在不同分辨率水平上对酵母渗透适应进行建模。
J Bioinform Comput Biol. 2013 Apr;11(2):1330001. doi: 10.1142/S0219720013300013. Epub 2013 Jan 9.

引用本文的文献

1
A modular model integrating metabolism, growth, and cell cycle predicts that fermentation is required to modulate cell size in yeast populations.一个整合了代谢、生长和细胞周期的模块化模型预测,发酵对于调节酵母群体中的细胞大小是必需的。
PLoS Comput Biol. 2025 Jul 21;21(7):e1013296. doi: 10.1371/journal.pcbi.1013296. eCollection 2025 Jul.

本文引用的文献

1
pyPESTO: a modular and scalable tool for parameter estimation for dynamic models.pyPESTO:用于动态模型参数估计的模块化和可扩展工具。
Bioinformatics. 2023 Nov 1;39(11). doi: 10.1093/bioinformatics/btad711.
2
"Be sustainable": EOSC-Life recommendations for implementation of FAIR principles in life science data handling.“保持可持续性”:EOSC-Life 关于在生命科学数据处理中实施 FAIR 原则的建议。
EMBO J. 2023 Dec 1;42(23):e115008. doi: 10.15252/embj.2023115008. Epub 2023 Nov 15.
3
Elucidating yeast glycolytic dynamics at steady state growth and glucose pulses through kinetic metabolic modeling.
通过动力学代谢建模阐明酵母糖酵解在稳态生长和葡萄糖脉冲时的动态。
Metab Eng. 2023 May;77:128-142. doi: 10.1016/j.ymben.2023.03.005. Epub 2023 Mar 23.
4
A dynamical stochastic model of yeast translation across the cell cycle.酵母细胞周期中翻译过程的动态随机模型。
Heliyon. 2023 Jan 26;9(2):e13101. doi: 10.1016/j.heliyon.2023.e13101. eCollection 2023 Feb.
5
UniProt: the Universal Protein Knowledgebase in 2023.UniProt:2023 年的通用蛋白质知识库。
Nucleic Acids Res. 2023 Jan 6;51(D1):D523-D531. doi: 10.1093/nar/gkac1052.
6
Ensembl 2023.Ensembl 2023.
Nucleic Acids Res. 2023 Jan 6;51(D1):D933-D941. doi: 10.1093/nar/gkac958.
7
A yeast cell cycle model integrating stress, signaling, and physiology.一个整合应激、信号传导和生理学的酵母细胞周期模型。
FEMS Yeast Res. 2022 Jun 30;22(1). doi: 10.1093/femsyr/foac026.
8
Whole-cell modeling in yeast predicts compartment-specific proteome constraints that drive metabolic strategies.酵母中的全细胞建模预测了驱动代谢策略的特定区室蛋白质组限制。
Nat Commun. 2022 Feb 10;13(1):801. doi: 10.1038/s41467-022-28467-6.
9
A predictive model of gene expression reveals the role of network motifs in the mating response of yeast.一个基因表达的预测模型揭示了网络基元在酵母交配反应中的作用。
Sci Signal. 2021 Feb 16;14(670):eabb5235. doi: 10.1126/scisignal.abb5235.
10
PEtab-Interoperable specification of parameter estimation problems in systems biology.系统生物学中参数估计问题的PEtab可互操作规范。
PLoS Comput Biol. 2021 Jan 26;17(1):e1008646. doi: 10.1371/journal.pcbi.1008646. eCollection 2021 Jan.