A Linear Syst0ems Toolkit for Biology

生物学是复杂的；细胞是由上千种蛋白质、相似数量的代谢物和数以万计的基因组成的。生物学研究的一个目标是了解这种复杂性如何带来生命的功能。实现这一目标的一种方法是理解组成单元的数千个组件之间的连接。测量所有组成部分之间的联系是具有挑战性的，特别是因为细胞是不断变化的动态系统。准确描述发生在细胞内的动态网络相互作用是实现改良作物、粮食安全和新药所需的进步所必需的。我们采用了一个来自工程学的新工具集，以数学形式描述生物网络。我们为每个连接建立模型，用来预测系统将如何随时间变化，这对于发现细胞如何对温度、激素或药物变化等信号做出反应非常有用。我们的新数学工具集允许研究人员识别和量化生物网络中的变化，这些变化可以导致发现基因或途径，这些基因或途径涉及对压力或药物的反应，并可能成为疾病的基础。我们的新数学工具集将在理解广泛的细胞系统方面具有广泛的效用，从药物对人体的影响到作物对环境变化或害虫攻击的反应。我们开发的一种测量生物网络如何变化的工具对于理解生物学、治疗疾病和改善作物植物以提供增强的粮食安全非常重要。我们建议发展这种所谓的Nu差距分析，作为生物学家的实用工具。在我们的实现中，我们使用简单的线性模型识别和描述生物系统中的连接。Nu间隙测量的是在不同条件下获得的连接的数学描述之间的差异，例如对药物或环境压力的反应。为了开发Nu缺口作为一种实用工具，我们将开展一项随着时间的推移而增加复杂性的研究计划。这将允许对Nu差距分析进行严格的测试、开发和部署。首先，我们将对基于虚构数据集的模型进行理论分析，这些模型是专门为评估Nu gap的优势和局限性而设计的。这将告知工具集的应用在哪里是最好的，相反，在Nu差距可能不太有用的情况下。在对系统有了良好的理论认识之后，我们将把Nu隙应用到我们实验室获得的真实世界数据中。我们将开始使用数据来描述模式植物拟南芥基因表达的昼夜节律调节。一个主要的目标将是研究药理学和遗传扰动对昼夜节律系统的影响。两者都深刻地影响生物钟的功能，但它们影响生物钟的机制尚不确定。我们将从研究模式植物拟南芥生物钟的基本特性转向使用线性建模和Nu gap分析来描述主要作物大麦的生物钟。生物钟调节着许多重要的农艺性状，如开花时间、结实率和耐寒性。我们的研究有可能为育种者提供有用的基因靶标。认识到生物系统不仅仅是遗传成分之间的一系列相互作用，我们将扩展我们的分析，以纳入细胞的生理学，例如细胞质中钙浓度的变化，这是应激条件下信号传导的关键调节因素。

Biology is complex; cells are made up of 1000s of proteins, a similar number of metabolites and tens of thousands of genes. A goal of biological research is to understand how this complexity brings about the functions of life. One way to achieve this goal is to understanding the connections between the 1000s of components that make up cells. Measuring the connections between all the components is challenging, particularly because cells are dynamical systems that are constantly changing. Accurate descriptions of the dynamical network interactions that take place in a cell are required to make the advances required for improved crops for food security and new medicines.We have adapted a new tool set from Engineering to describe biological networks in a mathematical form. We make models of each of the connections which are used to predict how the system will change over time, which is very useful in discovering how cells respond to signals such as changes in temperature, hormones or drugs. Our new mathematical tool set allows researchers to identify and quantify the changes in a biological network, which can lead to the discovery of the gene(s) or pathways that are involved in responses to stresses or drugs and might underlie disease. Our new mathematical tool set will have wide utility in understanding a wide range of cellular systems, from the effects of drugs in humans to the response of a crop plant to environmental changes or attack by pests. Our development of a tool that measures how biological networks change is important for understanding biology, curing disease and improving crop plants to provide enhanced food security. We propose to develop this so called Nu gap analysis as a practical tool for biologists. In our implementation, we identify and describe connections in biological systems using simple liner models. The Nu gap measures the difference between the mathematical descriptions of the connections obtained in different conditions, such as following a response to a drug, or an environmental stress. To develop the Nu gap as a practical tool we will undertake a research programme that increases with complexity over time. This will permit rigorous testing, development and deployment of Nu gap analyses. First, we will perform theoretical analyses of the Nu gap on models derived from fabricated datasets designed specifically to assess the strengths and limitations of the Nu gap. This will inform as to where application of the toolset would be best, and conversely the situations where the Nu gap might be less informative. Having developed good theoretical understanding of the system, we will apply the Nu gap to real world data obtained by our laboratories. We will begin using data describing the circadian regulation of gene expression in the model plant Arabidopsis. A major goal will be to investigate the effect of a pharmacological and a genetic perturbation to the circadian system. Both profoundly affect the functioning of the circadian clock, but the mechanisms by which these affect the circadian clock is uncertain.We will move from investigating the fundamental properties of the circadian clock in the model plant Arabidopsis to using linear modelling and Nu gap analyses to describe the circadian clock in a major crop, barley. The circadian clock regulates many important agronomic traits such as flowering time, seed set and cold tolerance. Our studies have the potential to inform breeders of useful gene targets. Recognising that biological systems are more than a series of interactions between genetic components we will extend our analysis to incorporate the physiology of the cell, such as changes in the concentration of calcium in the cytosol, which act as key regulators of signalling in stressful conditions.