Kimmel Marek
Department of Statistics and Bioengineering, Rice University, 2102 Duncan Hall, 6100 Main St., 77005, Houston, TX, USA,
Adv Exp Med Biol. 2014;844:119-52. doi: 10.1007/978-1-4939-2095-2_7.
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.
本章提出了一种造血过程建模的新观点,综合了确定性方法和随机方法。随机模型适用于机会起主导作用的情况,例如细胞数量较少时,或在随机突变的情况下,而确定性模型对于大规模的正常造血过程更为重要。新型模型即将出现。这些模型试图考虑诸如造血微环境等分布式环境及其对动力学的影响。这种结构和随机事件的混合效应在很大程度上尚不清楚,对建模而言既是挑战也是机遇。我们的讨论分别在确定性建模和随机建模的标题下进行;然而,两者之间的联系也经常被提及。包含了四个案例研究以阐明重要示例。我们还为读者提供了一份确定性和随机动力学的入门知识。