title: Stochasticity and determinism in models of hematopoiesis.
abstract: This chapter represents a novel view of modeling in hematopoiesis, synthesizing both deterministic and stochastic approaches. Whereas the stochastic models work in situations where chance dominates, for example when the number of cells is small, or under random mutations, the deterministic models are more important for large-scale, normal hematopoiesis. New types of models are on the horizon. These models attempt to account for distributed environments such as hematopoietic niches and their impact on dynamics. Mixed effects of such structures and chance events are largely unknown and constitute both a challenge and promise for modeling. Our discussion is presented under the separate headings of deterministic and stochastic modeling; however, the connections between both are frequently mentioned. Four case studies are included to elucidate important examples. We also include a primer of deterministic and stochastic dynamics for the reader's use.
authors.affiliation: Department of Statistics and Bioengineering, Rice University, 2102 Duncan Hall, 6100 Main St., 77005, Houston, TX, USA, kimmel@rice.edu.
authors.forename: Marek
authors.initials: M
authors.lastname: Kimmel
mesh_terms: D000818:Animals; D063646:Carcinogenesis / Q000235:genetics; D018450:Disease Progression; D025461:Feedback, Physiological; D033141:Genetic Determinism; D006410:Hematopoiesis / Q000502:physiology*; D006801:Humans; D007938:Leukemia / Q000235:genetics / Q000473:pathology; D008954:Models, Biological; D009154:Mutation; D013269:Stochastic Processes