Stochastic Modeling of Multi Type Cell Systems

描述(由申请人提供)：我们在NIH/NINDS Grant RO1 NS39511的赞助下进行的研究的最重要成果是少突胶质细胞体外发育的随机模型，该模型已针对几组实验数据进行了测试。建立在这个模型上的新的估计技术允许根据生物学上有意义的参数来分析潜在的过程。这些结果为设计推论程序提供了坚实的基础，这些推论程序是分析相关活体研究非常必要的。这项拟议研究的总体目标是发展这种程序，特别关注脊髓的胚胎发育。这里的主要挑战是，发育中的脊髓中少突胶质细胞前体的动力学是高度非平稳的。提出了一种分析和模拟技术相结合的方法来解决这一问题。我们最近的分析结果使这个问题变得容易理解。所提出的随机模型具有足够的灵活性来描述所研究的实验系统中细胞动力学的复杂模式。生物学实验将被特别设计，以充分利用拟议的建模技术和计算算法的力量。这种方法将提供对正常脊髓细胞发育的详细了解，以及在缺铁的病理条件下。

DESCRIPTION (provided by applicant): The most significant outcome of our studies conducted under the auspices of NIH/NINDS Grant RO1 NS39511 is a stochastic model of in vitro development of oligodendrocytes, which has been tested against several sets of experimental data. New estimation techniques built on this model allow analysis of the underlying processes in terms of biologically meaningful parameters. These results provide a solid groundwork for designing inferential procedures that are very much needed to analyze relevant in vivo studies. The general objective of the proposed research is to evolve such procedures with a special focus on embryonic development of the spinal cord. The major challenge here is that the dynamics of oligodendrocyte precursors in the developing spinal cord are highly non-stationary. A combination of analytical and simulation techniques is proposed as a constructive solution to this problem. Our recent analytical results make the problem approachable. The proposed stochastic model is sufficiently flexible to describe the complex patterns of cell dynamics in the experimental system under study. Biological experiments will be specially designed to fully utilize the power of the proposed modeling techniques and computational algorithms. This approach will provide a detailed understanding of cell development in the normal spinal cord, and in the pathological condition of iron deficiency.