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Here, we present a novel and simple procedure to identify dFBA parameters that are relevant for model calibration.
First, the choice of noise distribution assumption is highly relevant for model accuracy, as the worst result is 79%and74%4% higher than the lowest RMAE obtained for the AMS and GEFCom2014 datasets, respectively.
Let us note that when few parameters are identified as relevant for model dynamics, the previous analysis is performed for each of them trying to discover multiple dependencies.
Future work will include developing similar models for TFs from other structural classes and organisms, as well as refining the feature selection procedure and testing other feature selection methods (Maldonado and Weber, 2010; Nguyen and de la Torre, 2010; Yang and Ong, 2010) that might help us identify sequence features relevant for model accuracy.
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Elucidation of the factors caused denaturation is relevant for modeling interaction of proteins with natural polyelectrolytes.
This leads to introducing the taxonomy of deeper-order variables and interaction variables relevant for modeling the physical system.
The presented results may be relevant for modelling various types of nanotubes which, according to the latest experimental findings, possess strong material anisotropy.
As the uncertainty analyst does not know which influences are relevant for modelling the dependent variable, the sample space Ω contains 2K models of the general form y = {alpha}_{gamma } + {beta}_{gamma }{X}_{gamma } + varepsilon (13).
Though our study is limited in scope, we expect our results to remain relevant for models with a large number of parameters and other types of left right hidden Markov models.
The present results are obviously relevant for modeling the interface between word naming and speech production, with the inclusion of stress assignment, which is rather neglected in existing computational models.
These are especially relevant for models involving gene regulation.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com