Tuyển tập các báo cáo nghiên cứu về y học được đăng trên tạp chí y học quốc tế cung cấp cho các bạn kiến thức về ngành y đề tài: Stochastic modeling of oligodendrocyte generation in cell culture: model validation with time-lapse data | Theoretical Biology and Medical Modelling BioMed Central Research Open Access Stochastic modeling of oligodendrocyte generation in cell culture model validation with time-lapse data Ollivier Hyrien1 Ibro Ambeskovic2 Margot Mayer-Proschel2 Mark Noble2 and Andrei Yakovlev 1 Address Department of Biostatistics and Computational Biology University of Rochester 601 Elmwood Avenue Rochester New York 14642 USA and 2Department of Biomedical Genetics University of Rochester 601 Elmwood Avenue Rochester New York 14642 USA Email Ollivier Hyrien - Ollivier_Hyrien@ Ibro Ambeskovic - Ibro_Ambeskovic@ Margot Mayer-Proschel - Margot_Mayer-Proschel@ Mark Noble - Mark_Noble@ Andrei Yakovlev - Andrei_Yakovlev@ Corresponding author Published 17 May 2006 Received 06 April 2006 Theoretical Biology and Medical Modelling 2006 3 21 doi 1742-4682-3-21 Accepted I7 May 2006 This article is available from http content 3 1 21 2006 Hyrien et al licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License http licenses by which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. Abstract Background The purpose of this paper is two-fold. The first objective is to validate the assumptions behind a stochastic model developed earlier by these authors to describe oligodendrocyte generation in cell culture. The second is to generate time-lapse data that may help biomathematicians to build stochastic models of cell proliferation and differentiation under other experimental scenarios. Results Using time-lapse video recording it is possible to follow the individual evolutions of different cells within each clone. This experimental technique is very laborious and cannot replace model-based quantitative inference from clonal data. However .
