Embryo alignment is a two-step process: first embryos are aligned coarsely to the morphological template; second they are finely aligned to the registration template using the DIG ftz gene expression pattern.
Alignment is a computationally intensive process, and many computer programs (e.g., BWA aligner [ Li and Durbin, 2009]) have been devised that implement and optimize alignments according to various measures of similarity.
The alignment is an iterative process involving nonlinear constrained optimization, which forces datapoints to lie outside the nominal model under a specific order of priority.
In general, the alignment is an iterative process beginning with coarse features of the data set, for example, center of mass of each particle image, followed by grouping and averaging of individual images.
An important consideration in selecting a reference alignment is its underlying quality, yet manually curating a reference alignment is a tedious and painstaking process.
The alignment is a crucial part of the process, for the resolution of the reconstructed 3-D structures are limited to the accuracy in the alignment.
This paper introduces the BITAM (Business IT Alignment Method) which is a process that describes a set of twelve steps for managing, detecting and correcting misalignment.
Ontology alignment is the process of determining correspondences between ontology concepts.
Graph alignment is the process of mapping nodes and edges between graphs such that conserved subgraphs can be identified.
The alignment is processed with the program VISTA (13) using the default parameters (minimum length: 100 nt, minimum identity: 75%, excluded exons).
