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We investigate the combination of the three quasi-Newton methods with three different line-search methods either based on bisection, quadratic interpolation, or cubic interpolation.
Multi-step Mori-Tanaka mean-field homogenization methods, either based on known microstructural arrangement in the composite, or property contrast between the constituents, are applied to predict the composite thermal conductivity.
Confidence intervals can be obtained following standard asymptotic methods either based on a normal approximation of the likelihood surface or on the support curve [20].
Furthermore, some graph-theoretic methods either based on clustering or on heuristic search have also been introduced in the field of motif discovery [ 26– 28].
Different methods, either based on a de Bruijn graph [Velvet (Zerbino and Birney, 2008), ABySS (Simpson et al., 2009) and SPAdes (Bankevich et al., 2012)] or on a greedy approach [SSAKE, Edena (Hernandez et al., 2008)], are available in Orione.
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Thus, generally speaking, our method, either based on TFDF or F score, is robust to session-to-session transfers.
These methods are either based on bioinformatic/statistical approaches or physicochemical methods that produce an averaged signal from all residues of a protein, hence it is not known whether all residues of these domains are unstructured, or if a short sequence motif (e.g. residues within the conserved DELLA or TVHYNP motif) could possibly form secondary or tertiary structures.
Data driven methods are either based on a single variable or on multi-variable imputation.
The existing methods are either based on supervised classifiers in which the presence of true spikes has to be readily available and identifiable to train the algorithm during a learning phase, or they are template based, which rely on pre-specified spike characteristics such as amplitude and duration of the discharges.
Binning methods are either based on clustering or classification.
Such a transition network, which overcomes the fundamental limitations of reaction-coordinate-based methods, can be constructed either based on the features of the energy landscape, or from molecular dynamics simulations.
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