发帖
雷达卡
摘要翻译：
噬菌体λ是现代分子生物学中研究最多的生物模型之一。在过去的50年里，关于这种生物模型的定量实验知识已经在各个层次上积累：物理、化学、基因组学、蛋白质组学、功能等。它的所有组成部分都已知道了一个很大的细节。理论上的任务是整合其组成部分，使有机体以和谐的方式定量地工作。这将检验我们对生物学的理解，并为进一步的探索和应用奠定坚实的基础，这是系统生物学的一个明显目标。其中一个突出的挑战是所谓的稳定性难题：生物观察到的鲁棒性和基于已知实验值的数学重建。在这一章中，我们回顾了最近在解决这个问题上的理论和实验努力。重点讨论了最小定量模型，在此模型中，实验和数值模拟取得了成功的一致性。本文还从广义建模的角度讨论了一种新的随机动力结构分析方法。
---
英文标题：
《Efficiency, Robustness and Stochasticity of Gene Regulatory Networks in
Systems Biology: lambda Switch as a Working Example》
---
作者：
X. Zhu, L. Yin, L. Hood, D. Galas, and P. Ao
---
最新提交年份：
2006
---
分类信息：
一级分类：Quantitative Biology 数量生物学
二级分类：Subcellular Processes 亚细胞过程
分类描述：Assembly and control of subcellular structures (channels, organelles, cytoskeletons, capsules, etc.); molecular motors, transport, subcellular localization; mitosis and meiosis
亚细胞结构（通道、细胞器、细胞骨架、囊膜等）的组装和控制；分子马达；转运；亚细胞定位；有丝分裂和减数分裂
--
一级分类：Physics 物理学
二级分类：Other Condensed Matter 其他凝聚态物质
分类描述：Work in condensed matter that does not fit into the other cond-mat classifications
在不适合其他cond-mat分类的凝聚态物质中工作
--
一级分类：Physics 物理学
二级分类：Adaptation and Self-Organizing Systems 自适应和自组织系统
分类描述：Adaptation, self-organizing systems, statistical physics, fluctuating systems, stochastic processes, interacting particle systems, machine learning
自适应，自组织系统，统计物理，波动系统，随机过程，相互作用粒子系统，机器学习
--
一级分类：Quantitative Biology 数量生物学
二级分类：Molecular Networks 分子网络
分类描述：Gene regulation, signal transduction, proteomics, metabolomics, gene and enzymatic networks
基因调控、信号转导、蛋白质组学、代谢组学、基因和酶网络
--
一级分类：Quantitative Biology 数量生物学
二级分类：Other Quantitative Biology 其他定量生物学
分类描述：Work in quantitative biology that does not fit into the other q-bio classifications
不适合其他q-bio分类的定量生物学工作
--
---
英文摘要：
Phage lambda is one of the most studied biological models in modern molecular biology. Over the past 50 years quantitative experimental knowledge on this biological model has been accumulated at all levels: physics, chemistry, genomics, proteomics, functions, and more. All its components have been known to a great detail. The theoretical task has been to integrate its components to make the organism working quantitatively in a harmonic manner. This would test our biological understanding and would lay a solid fundamental for further explorations and applications, an obvious goal of systems biology. One of the outstanding challenges in doing so has been the so-called stability puzzle of lambda switch: the biologically observed robustness and its difficult mathematical reconstruction based on known experimental values. In this chapter we review the recent theoretical and experimental efforts on tackling this problem. An emphasis is put on the minimum quantitative modeling where a successful numerical agreement between experiments and modeling has been achieved. A novel method tentatively named stochastic dynamical structure analysis emerged from such study is also discussed within a broad modeling perspective.
---
PDF链接：
https://arxiv.org/pdf/q-bio/0512007
京公网安备 11010802022788号
