Computational Biology in Systems Immunology and Infectious Disease Modeling

现代技术现在可以在全球水平上分析免疫反应和宿主与病原体的相互作用，范围从细胞内信号网络到单个细胞行为，再到组织、器官甚至整个有机体的功能。挑战不仅是收集这种方法允许的大量数据，而且还在于组织信息的方式，以增强我们对免疫系统如何运行或病原体如何影响宿主的理解。 定量计算机模拟作为探索我们对细胞行为理解的极限的有价值的工具，正变得越来越重要。细胞生物学中计算建模的一个主要障碍是，将定性的生物学模型转换为计算模型需要工程师/数学家的干预，因为他们是生物学假设及其理论和计算表示之间的接口。PSIIM计算生物学小组正在开发的软件消除了由人完成翻译的必要性，从而降低了生物机制过于简化或非生物学家在翻译过程中丢失重要细节的风险。该软件提供了直观的图形界面，并结合了最先进的仿真技术。 我们2008/2009年工作的重点之一是开发一种技术，使创建计算机模拟成为可能，该计算机模拟将细胞信号过程的详细生化表示与再现局部招募和组织信号组件的效果所需的空间分辨率相结合。活动的另一个重点是创建一个数据库和数据库接口系统，将计算模型与实验数据和外部产生的蛋白质组信息相结合。 最后，高效的随机模拟能力和模拟形态细胞可塑性的技术目前正被添加到软件算法中。

Modern technology now allows the analysis of immune responses and host-pathogen interactions at a global level, across scales ranging from intracellular signaling networks, to individual cell behavior, to the functioning of a tissue, organ, and even the whole organism. The challenge is not only to collect the large amounts of data such methods permit, but also to organize the information in a manner that enhances our understanding of how the immune system operates or pathogens affect their hosts. Quantitative computer simulations are gaining importance as valuable tools for probing the limits of our understanding of cellular behavior. A major roadblock on the way to computational modeling in cell biology has been that the translation of qualitative biological models into computational models required the intervention of engineers/mathematicians as interfaces between biological hypotheses and their theoretical and computational representations. The software being developed by the computational biology group of the PSIIM eliminates the necessity of having this translation done by a person and thereby reduces the risk of oversimplification of biological mechanisms or the loss of important details in the course of translation by a non-biologist. The software offers an intuitive graphical interface combined with state-of-the-art simulation technology. One focus of our work in 2008/2009 has been to develop the technology that makes it possible to create computer simulations that combine detailed biochemical representation of cellular signaling processes with the spatial resolution necessary to reproduce the effects of localized recruitment and organization of signaling components. Another focus of activity has been the creation of a database and database interface system that couples the computational models to experimental data and externally generated proteomic information. Finally, efficient stochastic simulation capabilities and the technology to simulate morphological cellular plasticity are currently being added to the softwares algorithms.