Cell‐based allometry: an approach for evaluation of complexity in morphogenesis

Author:

Tarihi Ali1,Tarihi Mojtaba2,Tiraihi Taki3

Affiliation:

1. Department of Computer Engineering Faculty of Computer Science and Engineering Shahid Behshti University Tehran 19839‐69411 Iran

2. Department of Computer Engineering Sharif University of Technology Tehran 11365‐11155 Iran

3. Department of Anatomical Sciences School of Medical Sciences Tarbiat Modares University Tehran 14117‐13116 Iran

Abstract

BackgroundMorphogenesis is a complex process in a developing animal at the organ, cellular and molecular levels. In this investigation, allometry at the cellular level was evaluated.MethodsGeometric information, including the time‐lapse Cartesian coordinates of each cell’s center, was used for calculating the allometric coefficients. A zero‐centroaxial skew‐symmetrical matrix ( CSSM), was generated and used for constructing another square matrix (basic square matrix: BSM), then the determinant of BSM was calculated ( d). The logarithms of absolute d (Lad) of cell group at different stages of development were plotted for all of the cells in a range of development stages; the slope of the regression line was estimated then used as the allometric coefficient. Moreover, the lineage growth rate (LGR) was also calculated by plotting the Lad against the logarithm of the time. The complexity index at each stage was calculated. The method was tested on a developing Caenorhabditis elegans embryo.ResultsWe explored two out of the four first generated blastomeres in C. elegans embryo. The ABp and EMS lineages show that the allometric coefficient of ABp was higher than that of EMS, which was consistent with the complexity index as well as LGR.ConclusionThe conclusion of this study is that the complexity of the differentiating cells in a developing embryo can be evaluated by allometric scaling based on the data derived from the Cartesian coordinates of the cells at different stages of development.

Publisher

Wiley

Subject

Applied Mathematics,Computer Science Applications,Biochemistry, Genetics and Molecular Biology (miscellaneous),Modeling and Simulation

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