The Synthesis of Probabilistic Prediction & Mechanistic Modelling within a Computational & Systems Biology Context

在系统生物学的背景下，抽象的计算模型和生物实验研究之间的多学科相互作用可以取得的协同进展，将对我们理解一些最重要的生物系统做出重大贡献，这些系统与许多严重疾病的发生有关，如癌症。然而，由于生物学数据不可避免地固有的不确定性、噪声和相对稀缺性，重要的是在系统生物学的背景下，通过在概率推理框架内正式嵌入机械模型来实现基于可靠证据的科学推理。机械建模和概率推理的综合提供了极好的机会，通过定义系统组件和推断它们如何动态地相互作用，在多个层面上理解生物系统和过程方面取得进一步重大进展。统计机器学习方法在计算和系统生物学研究中扮演着重要的角色，在这一领域的应用提出了许多重要的方法论挑战。然而，成功的计算和系统生物学研究最重要的方面之一是它必须直接与世界级的实验生物学家合作进行。该奖学金的一个突出特点是，它与国际领先的癌症研究人员、蛋白质组学技术专家、生物化学家和植物生物学家建立了六个令人兴奋的合作，他们都完全致力于成功地推动一个潜在的突破性多学科系统生物学研究计划，如本提案所述。生物科学中的三个重要应用领域将塑造和指导在本次奖学金期间进行的研究。这些应用是不同的，但在建模和推理方面存在重叠，这对确保一致和连贯的研究路线很重要。它们还被选中，因为它们在研究细胞机制方面具有重要意义，这些机制是细胞功能的基础，其中一些与某些严重疾病有关。此外，申请人与从事这些生物研究的世界级实验室有实质性的持续合作。这确保拟议的研究方案侧重于现实的方法问题，这些问题将对每个领域提出的重大科学问题产生直接影响，并有助于计算科学和推论科学。第一个应用程序将开发癌症生物学家在对观察到的MAPK途径动态背后的结构进行推理时所需的推理工具，这些工具将被用于与Beatson癌症研究所合作对该途径进行的大规模研究。第二个应用将与格拉斯哥大学植物科学小组一起进行，将试图以基于模型的推理方式阐明在大豆和拟南芥中观察到的昼夜节律时钟器官专一性的显著现象，此外还将对细胞周期中的转录调控模型进行研究。最终的应用将调查一些与临床转录学和蛋白质组学相关的公开问题，其中识别可能的目标基因和蛋白质对癌症研究人员在他们的研究中至关重要，在这种情况下是乳腺癌和卵巢癌。这项研究将直接与癌症研究所合作进行，那里正在进行一项关于BRCA1和2突变与乳腺癌和卵巢癌有关的正在进行的研究。

The synergistic advances that can be made by the multidisciplinary interplay between abstracted computational modelling and biological experimental investigation within a system biology context are poised to make major contributions to our understanding of some of the most important biological systems implicated in the genesis of many serious diseases such as cancer. However, due to the unavoidable inherent levels of uncertainty, noise and relative scarcity of biological data it is vital that sound evidential based scientific reasoning be enabled within a systems biology context by formally embedding mechanistic models within a probabilistic inferential framework. The synthesis of mechanistic modelling & probabilistic inference provides outstanding opportunities to make further significant advances in understanding biological systems and processes at multiple levels, by defining system components and inferring how they dynamically interact. There is a major role that statistical machine learning methodology has to play in both computational & systems biology research and a number of important methodological challenges are presented by applications working at this interface.However, one of the most important aspects of successful computational & systems biology research is that it must be conducted in direct collaboration with world-class experimental biologists. An outstanding feature of this Fellowship is that it has set in place six exciting collaborations with internationally leading cancer researchers, proteomics technologists, biochemists and plant biologists who are all fully committed to successfully driving forward a potentially groundbreaking multidisciplinary systems biology research programme as detailed in this proposal. Three important application areas within biological science will shape and direct the research to be undertaken during this Fellowship. The applications are distinct, yet overlap in terms of the modelling & inferential issues which each present and this is important in ensuring a consistent and coherent line of research. They have also been selected for their major importance in the study of cellular mechanisms which are fundamental to cell function, some of which are implicated in certain serious diseases. In addition, the applicant has substantive ongoing collaborations with world-class laboratories engaged in these biological investigations. This ensures the proposed research programme is focused on realistic methodological problems which will have a direct impact on the major scientific questions being asked within each area, as well contributing to the computational and inferential sciences. The first application will develop the inferential tools required by cancer biologists when reasoning about the structures underlying the observed dynamics of the MAPK pathway and these tools will be employed in a large scale study of this pathway in collaboration with the Beatson Institute of Cancer Research. The second application, to be conducted with the Plant Sciences group at the University of Glasgow, will seek to elucidate, in a model-based inferential manner, the remarkable observed phenomenon of organ specificity of the circadian clock in soybean and Arabidopsis, in addition a study of models of transcriptional regulation in the cell-cycle will be conducted. The final application will investigate a number of open issues associated with clinical transcriptomics and proteomics where the identification of possible target genes and proteins is of vital importance to cancer researchers in their studies of, in this case breast and ovarian cancer. This study will be conducted in direct conjunction with the Institute of Cancer Research where an ongoing study of BRCA1&2 mutations implicated in breast and ovarian cancer is underway.