Indistinguishability analysis for model discrimination in Systems Biology: A Feasibility Study applied to Bacterial Peptidoglycan Biosynthesis

系统生物学中模型辨别的不可区分性分析：应用于细菌肽聚糖生物合成的可行性研究

• 批准号: EP/E057535/1
• 负责人: Neil Evans
• 金额: $ 34.65万
• 依托单位: University of Warwick
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2007
• 资助国家: 英国
• 起止时间: 2007 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FE057535%2F1
• 关键词: Indistinguishability; analysis; model; discrimination; Systems

In Systems Biology the mathematical/network models that are generated invariably include large numbers of variables with numerous parameters, many of which are unknown, or cannot be directly measured. With such highly complex systems there are often few direct measurements that can be made and limited access for inputs or perturbations. These limitations cause immense problems when investigating the existence of hidden mechanisms or attempting to estimate unknown parameters and these problems severely hinder validation of the model. It is therefore highly desirable to have a formal approach to determine what additional inputs and/or measurements are necessary in order to reduce, or remove, these limitations and permit the derivation of models that can be used for practical purposes with greater confidence.The purpose of this project is to ascertain the possible effectiveness of using structural indistinguishability techniques in model discrimination within Systems Biology networks. This is the important question of how to design an experiment, or experiments, to allow discrimination between two (or more) competing biological mechanisms. Structural indistinguishability for systems models is concerned with determining the uniqueness between possible candidates for the model (or mechanism) structure. The formal nature of the analysis performed in this project should permit the generation of a minimal set, or sets, of reactants that must be available for measurement in order to distinguish between competing reaction schemes. Structural identifiability can be considered as a special case of the structural indistinguishability problem and considers the uniqueness of the unknown model parameters from the input-output structure corresponding to proposed experiments for data collection. If parameter estimates are to be used to inform intervention or inhibition strategies, or other critical decisions, then it is essential that the parameters be uniquely identifiable. Once an appropriate scheme has been selected, a structural identifiability analysis will be performed, which should generate a similar set of reactants that must be available for measurement in order to guarantee uniqueness of the model parameters with respect to the responses measured. This analysis will be performed on parts of the overall system, that can themselves be considered as (sub)systems, and then the results will be combined in a novel way to test for the identifiability of the complete system.These theoretical techniques will be used to suggest innovative forms of measurement for a case study (Bacterial Peptidoglycan Biosynthesis) considered within the project. Understanding of the underlying biological process for the case study is essential for developing new strategies for dealing with antibiotic resistance. In addition, modelling of the unknown components within the case study will be driven by the results obtained from the theoretical analysis and data collected from appropriate biological experiments. In addition, the development of a new stopped flow spectrophotometer will have the capacity to collect simultaneous measurements, within a single reaction, from fluoresence changes upon formation of the enzyme substrate complex and absorbance changes upon product formation. These novel data will further inform and test the model.The overall aim of this project will be to develop, innovative, formal and generic methods for performing this analysis for models in Systems Biology. The approach will be to develop these generic tools via application to the exemplar system (Bacterial Peptidoglycan Biosynthesis), then to extend the results obtained to more general systems models.

在系统生物学中，生成的数学/网络模型总是包含大量具有众多参数的变量，其中许多是未知的，或者无法直接测量。对于这种高度复杂的系统，通常很少有直接测量可以进行，并且输入或扰动的访问有限。这些限制导致巨大的问题时，调查隐藏的机制的存在或试图估计未知的参数，这些问题严重阻碍了模型的验证。因此，非常希望有一个正式的方法来确定什么额外的输入和/或测量是必要的，以减少，或删除，这些限制，并允许推导出的模型，可以用于实际目的，具有更大的信心。本项目的目的是确定可能的有效性，使用结构不变性技术在系统生物学网络内的模型歧视。这是一个重要的问题，即如何设计一个或多个实验，以区分两个（或多个）竞争的生物机制。系统模型的结构不相容性涉及确定模型（或机制）结构的可能候选者之间的唯一性。在这个项目中进行的分析的正式性质应允许生成一个最小的一组或几组反应物，必须可用于测量，以区分竞争的反应方案。结构可识别性可以被认为是结构不可识别性问题的一种特殊情况，并考虑了与数据收集实验相对应的输入输出结构中未知模型参数的唯一性。如果要使用参数估计来告知干预或抑制策略或其他关键决策，则参数必须是唯一可识别的。一旦选择了合适的方案，将进行结构可识别性分析，这将产生一组相似的反应物，这些反应物必须可用于测量，以保证模型参数相对于测量的响应的唯一性。该分析将在整个系统的部分上进行，这些部分本身可以被视为（子）系统，然后将结果以一种新的方式组合起来，以测试整个系统的可识别性。这些理论技术将用于为项目中考虑的案例研究（细菌肽聚糖生物合成）提出创新的测量形式。了解案例研究的潜在生物学过程对于制定应对抗生素耐药性的新策略至关重要。此外，案例研究中未知成分的建模将由理论分析获得的结果和从适当的生物实验中收集的数据驱动。此外，一个新的停流分光光度计的发展将有能力收集同时测量，在一个单一的反应，从荧光变化后形成的酶底物复合物和吸光度变化后形成的产品。这些新的数据将进一步通知和测试模型。这个项目的总体目标将是开发，创新的，正式的和通用的方法来执行系统生物学模型的分析。该方法将开发这些通用的工具，通过应用到示范系统（细菌肽聚糖生物合成），然后将获得的结果扩展到更一般的系统模型。

项目成果

The use of a formal sensitivity analysis on epidemic models with immune protection from maternally acquired antibody

对具有母体获得性抗体免疫保护的流行病模型进行正式敏感性分析

• 发表时间: 2009
• 作者: Chapman J.D.

The structural identifiability of SIR type epidemic models with incomplete immunity and birth targeted vaccination

不完全免疫及出生定向接种SIR型流行病模型的结构识别

• 发表时间: 2008
• 作者: Chapman J.D.

Estimation of kinetic rate constants from surface plasmon resonance experiments

从表面等离子体共振实验估计动力学速率常数

• DOI: 10.1049/ic.2010.0300
• 发表时间: 2010
• 作者: Evans N

The input-output relationship approach to structural identifiability analysis

• DOI: 10.1016/j.cmpb.2012.10.012
• 发表时间: 2013-02-01
• 期刊: COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
• 影响因子: 6.1
• 作者: Bearup, Daniel J.;Evans, Neil D.;Chappell, Michael J.
• 通讯作者: Chappell, Michael J.