Microtubule-based nucleation results in a large sensitivity to cell geometry of the plant cortical array
Fig 9
Schematic overview of the LDD nucleation algorithm.
(A) The position in the simulation domain where a nucleation complex (tentatively) appears is selected randomly, with uniform distribution. (B) Such a position, represented by the blue dot, is the centre of the nucleation area (the area within in the black circle with exploration radius R). N meta-trajectories are drawn equidistant from one another and with random orientation. Meta-trajectories are drawn up until the boundary of the nucleation area or the lattice of the first intersecting microtubule, whichever is closer. (C) Whether the resulting nucleation is microtubule-based or unbound and, in the former case, the parent microtubule and the nucleation location, is decided stochastically with probability p(di) weighted over the length of meta-trajectories, according to Eq (4). (D) In a microtubule-based nucleation, the angles follow Eq (2) [17]: a newly-nucleated microtubule initially grows along the parent microtubule with probability , in the opposite direction with probability
, or branches to either side with probability
. The branching angle is determined according to a distribution that closely matches the data in [12] (Eq (2)).