STOCHASTIC MODELING OF MULTI TYPE CELL SYSTEMS

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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.