title: Stochastic branching model for hemopoietic progenitor cell differentiation.
abstract: We present algebraic expressions describing the predictions of a stochastic branching model for differentiation of hemopoietic progenitor cells. The model assumes that there is a fixed probability, p (0 less than or equal to p less than or equal to 1), that commitment to a differentiative event occurs per progenitor cell division for each daughter cell. The model describes properties of in vitro hemopoietic cell differentiation including the population structure at the time the first progenitor cell becomes committed, the number of committed progenitor cells engendered by a single progenitor cell, and the probability of eventual commitment of all daughter cells derived from a single progenitor or stem cell. Application of the model to experimental data obtained from erythroid cultures suggests that the observed data can be explained by the stochastic branching model alone without making the deterministic assumption that there is a differentiative hierarchy in the lineage of the progenitors of erythropoiesis (BFU-E). The qualitative and quantitative aspects of the proposed stochastic model are discussed in conjunction with other analogous stochastic branching models.
mesh_terms: D002455:Cell Division; D004912:Erythrocytes / Q000166:cytology / Q000378:metabolism; D004920:Erythropoiesis; D006410:Hematopoiesis; D006412:Hematopoietic Stem Cells / Q000166:cytology*; D006454:Hemoglobins / Q000096:biosynthesis; D006801:Humans; D008433:Mathematics; D008954:Models, Biological; D013269:Stochastic Processes
chemical_list: D006454:Hemoglobins