Sentence examples for unsupervised alignment from inspiring English sources

Unsupervised alignment algorithms would misleadingly align such similarities; this is for instance the case for the LOOM software used on the NCBO portal (Ghazvinian et al., 2009).

In the first case, we formulated a binding mode hypothesis for a series of 59 partial agonists at the human α 7 nicotinic receptor using an iterative unsupervised alignment procedure implemented in Open3DALIGN [2].

The most important contribution of the present unsupervised, alignment-free method should be to predict functions of increasingly vast quantity of function-unknown proteins derived from less characterized genomes, such as those studied in the metagenomic approaches.

Phylogenetic models for the conserved and non-conserved state were fitted to the referenced alignment using unsupervised learning.

MetSign[245] provides several bioinformatics tools for raw data deconvolution, metabolite putative assignment, peak list alignment, normalization, statistical significance tests, unsupervised pattern recognition, and time course analysis.

However, the existing alignment-free methods are all based on unsupervised learning strategy (e.g., PCA or hierarchical clustering).

Our bias-free subtomogram processing uses unsupervised hierarchical ascendant classification and averaging (HAC), a technique involving pairwise alignment of sub-tomograms and clustering based on similarity (Bartesaghi et al., 2008; Förster et al., 2008; Schmid and Booth, 2008), without the aid of a reference and without imposing symmetry at any point.

In order to deal with the severe case of unlabeled data, a method is proposed based on dynamic time alignment of Gaussian mixture model clusters for matching actions in an unsupervised temporal segmentation.

The stationary amino acid distributions π1, π2,..., π50 and class prior probability distribution τ are estimated using an unsupervised Expectation-Maximization algorithm (see Methods) in order to fit the Pfam alignments as closely as possible.

Pairwise global sequence alignments of the two monomer types (DMA1, 59 monomers; DMA2, 34 monomers) were used to perform unsupervised clustering predictions.

Pairwise alignments of all sequences represented in each 200 bp-window (MUSCLE) [ 60] were used to perform unsupervised clustering predictions.