Meli Gianfelice, Weber Tom S, Duffy Ken R
Hamilton Institute, Maynooth University, Co. Kildare, Ireland.
The Walter and Eliza Hall Institute of Medical Research, The University of Melbourne, Parkville, Australia.
J Math Biol. 2019 Jul;79(2):673-704. doi: 10.1007/s00285-019-01373-0. Epub 2019 May 8.
Motivated by a recently proposed design for a DNA coded randomised algorithm that enables inference of the average generation of a collection of cells descendent from a common progenitor, here we establish strong convergence properties for the average generation of a super-critical Bellman-Harris process. We further extend those results to a two-type Bellman-Harris process where one type can give rise to the other, but not vice versa. These results further affirm the estimation method's potential utility by establishing its long run accuracy on individual sample-paths, and significantly expanding its remit to encompass cellular development that gives rise to differentiated offspring with distinct population dynamics.
受最近提出的一种DNA编码随机算法设计的启发,该算法能够推断出源自共同祖细胞的一组细胞的平均代数,在此我们建立了超临界Bellman-Harris过程平均代数的强收敛性质。我们进一步将这些结果扩展到一种两类Bellman-Harris过程,其中一类可以产生另一类,但反之则不行。这些结果通过在个体样本路径上建立其长期准确性,并显著扩大其范围以涵盖产生具有不同种群动态的分化后代的细胞发育过程,进一步肯定了该估计方法的潜在效用。