A Gene-Complete Computational Model of Yeast

摘要 这项提议的目标是建立一个能够模拟完整生命的计算模型 单个酵母细胞的循环，考虑到所有注释的基因。这已经被称为 这是理解简单细胞的终极测试，它将彻底改变我们看待生物学的方式，通过 使我们能够检查主要细胞过程之间的相互作用，这些过程从来没有 以前学过的。我们将通过集成计算建模和 实验生物学，详细研究衰老和寿命控制。 要完成拟议的工作，必须解决几个智力方面的挑战 成功了。例如，我们构建全细胞模型的一个主要组成部分将是 依赖于新的建模方法的发展，适用于大规模。 此外，用于集成不同类型生物过程的模型的方法， 它们中的每一个都可以用不同的表示法进行最佳描述，这将是至关重要的。幸运的是， P.I.的特殊专长是对各种细胞过程进行建模，特别是 大规模集成不同的网络模型。 我们提议的工作不仅是为了通过建造一台全细胞计算机的最终测试 模型，而是让科学界和公众通过 用户友好的Web界面。该项目的一个可交付成果将是基于Web的平台，该平台 将允许用户跟踪和干扰生物过程，如DNA复制、RNA 转录和调控、蛋白质合成、代谢和细胞分裂。对于科学家来说， 平台将具有高级用户选项，以便其他研究人员可以调整我们的方法以适应 无论他们喜欢哪种细胞类型(S)。我们预计，这可能导致广泛的实施 使用计算建模和模拟来指导实验计划的研究 和生物发现。

Abstract The target of this proposal is to build a computational model that can simulate a complete life cycle of a single yeast cell, taking into account all of the annotated genes. This has been called ¿the ultimate test of understanding a simple cell¿ and will revolutionize how we view biology, by allowing us to examine interactions between major cellular processes which have never been studied before. We will demonstrate this point, integrating computational modeling and experimental biology, in a detailed study of aging and lifespan control. Several intellectual challenges will have to be addressed to complete the proposed work successfully. For example, a major component of our effort to build a whole-cell model will depend on the development of new modeling approaches, applicable at a large scale. Additionally, methods for the integration of models for different types of biological processes, each of which may be best described using different representation, will be critical. Fortunately, the particular expertise of the P.I. is in modeling a variety of cellular processes, and in particular integrating different network models at the large scale. Our proposed work aims not only to pass the ¿ultimate test¿ of building a whole-cell computer model, but to make it accessible to the scientific community and the general public through a user-friendly web interface. One deliverable of the project will be a web-based platform which will allow the user to track and perturb biological processes such as DNA replication, RNA transcription and regulation, protein synthesis, metabolism and cell division. For scientists, the platform will have advanced user options, so that other researchers can adapt our methods to whichever cell type(s) they prefer. We anticipate that this could lead to a broad implementation of research which uses computational modeling and simulation to guide experimental programs and biological discovery.