title: Self-organization of developing embryo using scale-invariant approach.
abstract: BACKGROUND
  Self-organization is a fundamental feature of living organisms at all hierarchical levels from molecule to organ. It has also been documented in developing embryos.
  
  
  METHODS
  In this study, a scale-invariant power law (SIPL) method has been used to study self-organization in developing embryos. The SIPL coefficient was calculated using a centro-axial skew symmetrical matrix (CSSM) generated by entering the components of the Cartesian coordinates; for each component, one CSSM was generated. A basic square matrix (BSM) was constructed and the determinant was calculated in order to estimate the SIPL coefficient. This was applied to developing C. elegans during early stages of embryogenesis. The power law property of the method was evaluated using the straight line and Koch curve and the results were consistent with fractal dimensions (fd). Diffusion-limited aggregation (DLA) was used to validate the SIPL method.
  
  
  CONCLUSIONS
  The fractal dimensions of both the straight line and Koch curve showed consistency with the SIPL coefficients, which indicated the power law behavior of the SIPL method. The results showed that the ABp sublineage had a higher SIPL coefficient than EMS, indicating that ABp is more organized than EMS. The fd determined using DLA was higher in ABp than in EMS and its value was consistent with type 1 cluster formation, while that in EMS was consistent with type 2.
authors.affiliation: College of Computer and Electrical Engineering, Shaheed Behshti University, Tehran, Iran.
authors.forename: Ali
authors.initials: A
authors.lastname: Tiraihi
authors.forename: Mujtaba
authors.initials: M
authors.lastname: Tiraihi
authors.forename: Taki
authors.initials: T
authors.lastname: Tiraihi
mesh_terms: D000818:Animals; D017173:Caenorhabditis elegans / Q000166:cytology / Q000196:embryology*; D019070:Cell Lineage; D004058:Diffusion; D004625:Embryo, Nonmammalian / Q000166:cytology / Q000196:embryology*; D047108:Embryonic Development; D008954:Models, Biological; D012044:Regression Analysis; D015053:Zygote / Q000166:cytology