STOCHASTIC MODELING OF MULTI TYPE CELL SYSTEMS

多类型细胞系统的随机建模

• 批准号: 6615577
• 负责人: ANDREI Y YAKOVLEV
• 金额: $ 41.07万
• 依托单位: UNIVERSITY OF ROCHESTER
• 依托单位国家: 美国
• 财政年份: 2001
• 资助国家: 美国
• 起止时间: 2001-07-01 至 2005-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6615577
• 关键词: apoptosis; cell cell interaction; cell differentiation; cell proliferation; computer simulation; developmental neurobiology; fibroblast growth factor; laboratory rat; mathematical model; model design /development; neurogenesis; oligodendroglia; platelet derived growth factor; stem cells

DESCRIPTION (Adapted from applicant's abstract): The objectives of this project are to provide general stochastic modeling techniques aimed at quantitative inferences from experimental data on the development of cell clones consisting of more than one distinct type of cells. The only restriction imposed on the class of models under consideration is that a given member of the class can be represented as a multi-type branching stochastic process. The goal is to develop methods of stochastic modeling and statistical inference that can be used with any appropriate data to produce the desired estimates. As part of previous attempts to understand fundamental principles that underlie the generation of terminally differentiated progeny from dividing precursor cells, the PI and collaborators have developed a stochastic model of clonal growth and differentiation of progenitor cells in vitro. The model provides a description of experimental data on O-2A progenitor cells obtained from optic nerves of 1 and 7 day-old rats. Preliminary results obtained from these studies provide the basis for further elaboration and generalization of the proposed methods for quantitative analysis of multi-type cell systems. The goal of the proposed application is to validate these methods further by computer simulations, experimental data analyses and testing alternative models and to extend these methods further to include more information from modern biology. The justification for the biological system chosen is that the data available from experiments with O-2A progenitor cells provide an excellent laboratory in which to evaluate general methods proposed in this project; the PI proposes to use the existing data and conduct new experiments for this purpose.

描述（改编自申请人的摘要）：本项目的目标 是提供一般的随机建模技术，旨在定量 根据细胞克隆发育的实验数据推断， 不止一种不同类型的细胞。唯一的限制是 考虑的一类模型是，类的给定成员可以是 表示为多类型分支随机过程。目标是 开发随机建模和统计推断的方法， 与任何适当的数据一起使用，以产生所需的估计值。的一部分 以前试图理解的基本原则， 从分裂的前体细胞产生终末分化的后代， PI和合作者开发了克隆生长的随机模型， 祖细胞的体外分化。该模型提供了一个描述 的实验数据的O-2A祖细胞获得的视神经1 和7日龄大鼠。这些研究的初步结果提供了 进一步拟订和推广拟议方法的基础 多类型细胞系统的定量分析。建议的目标 应用是通过计算机模拟进一步验证这些方法， 实验数据分析和测试替代模型，并扩展这些 方法进一步包括更多来自现代生物学的信息。的 选择生物系统的理由是， 用O-2A祖细胞进行的实验提供了极好的实验室， 评估本项目中提出的一般方法; PI建议使用 现有的数据，并为此目的进行新的实验。