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.

Agency
National Institute of Health (NIH)
Institute
National Institute of Neurological Disorders and Stroke (NINDS)
Type
Research Project (R01)
Project #
5R01NS039511-02
Application #
6540205
Study Section
Special Emphasis Panel (ZRG1-SSS-P (01))
Program Officer
Leblanc, Gabrielle G
Project Start
2001-07-01
Project End
2002-10-21
Budget Start
2002-07-01
Budget End
2002-10-21
Support Year
2
Fiscal Year
2002
Total Cost
$37,086
Indirect Cost
Name
University of Utah
Department
Internal Medicine/Medicine
Type
Schools of Medicine
DUNS #
City
Salt Lake City
State
UT
Country
United States
Zip Code
84112
Hyrien, Ollivier; Baran, Andrea (2016) Fast Nonparametric Density-Based Clustering of Large Data Sets Using a Stochastic Approximation Mean-Shift Algorithm. J Comput Graph Stat 25:899-916
Greminger, Allison R; Mayer-Pröschel, Margot (2015) Identifying the threshold of iron deficiency in the central nervous system of the rat by the auditory brainstem response. ASN Neuro 7:
Hyrien, Ollivier; Yanev, Nikolay M; Jordan, Craig T (2015) A test of homogeneity for age-dependent branching processes with immigration. Electron J Stat 9:898-925
Hyrien, O; Peslak, S A; Yanev, N M et al. (2015) Stochastic modeling of stress erythropoiesis using a two-type age-dependent branching process with immigration. J Math Biol 70:1485-521
Greminger, Allison R; Lee, Dawn L; Shrager, Peter et al. (2014) Gestational iron deficiency differentially alters the structure and function of white and gray matter brain regions of developing rats. J Nutr 144:1058-66
Chen, Rui; Hyrien, Ollivier (2014) ON CLASSES OF EQUIVALENCE AND IDENTIFIABILITY OF AGE-DEPENDENT BRANCHING PROCESSES. Adv Appl Probab 46:704-718
Hyrien, Ollivier; Yanev, Nikolay M (2012) Asymptotic behavior of cell populations described by two-type reducible age-dependent branching processes with non-homogeneous immigration(). Math Popul Stud 19:164-176
Lee, Dawn L; Strathmann, Frederick G; Gelein, Robert et al. (2012) Iron deficiency disrupts axon maturation of the developing auditory nerve. J Neurosci 32:5010-5
Tanner, Daniel C; Cherry, Jonathan D; Mayer-Pröschel, Margot (2011) Oligodendrocyte progenitors reversibly exit the cell cycle and give rise to astrocytes in response to interferon-?. J Neurosci 31:6235-46
Hyrien, Ollivier; Yanev, Nikolay M (2011) Two-Type Age-Dependent Branching Processes with Inhomogeneous Immigration as Models of Renewing Cell Populations. Pliska 20:81-108

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