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We first provide a constrained alignment framework applicable to the problem.
We provide a constrained alignment framework and a metabolic pathway alignment algorithm, CAMPways.
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A preferential constrained alignment algorithm calculates the proper compensation, or fixture offset, for any type of geometry to eliminate any possible shortage of material if possible, or orient the unavoidable area of missing material for appropriate rework.
We provide a formal description of our constrained alignment framework within the provided one-to-many pathway alignments model.
▪ To provide further depth to our understanding of the problem within the constrained alignment framework, we next state the following proposition, which may suggest a clue as to the point the computational intractability starts dissolving.
In order to calculate constraint scores for Agrp exons, the STAT sites, and the IREs, we modified the concept of an RS score, such that the score for constraint represents the sum of constrained alignment columns in these regions while ignoring unconstrained alignment columns.
We present our Constrained Alignment of Metabolic Pathways (CAMPways) algorithm designed for this purpose.
We note that our constrained alignment framework may trivially be generalized to undirected PPI networks.
However, some modifications are necessary to make our conflict graph model more useful in practical applications of the constrained alignment framework.
Step3-Final Alignment Expansion: The iterative process involving the first two steps aforementioned produces mappings based on tuples because of the conserved interaction maximization goal of the constrained alignment framework.
This constrained alignment can achieve even higher alignment precision and is more robust to distortions in subtomograms, even when only 6 to 8 initial rotation angle candidates are used.
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CEO of Professional Science Editing for Scientists @ prosciediting.com