Sentence examples for cluster discussion from inspiring English sources

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A coding dictionary was developed to organize the data and be able to better cluster discussion of the FMSD items.

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Given the proposed conversion of 20 25% of the remainder of the clusters into P-clusters (see Discussion), there is a yet-unknown FeS cluster(s) that comprises 40 50% of the total cluster population in this protein.

Due to the difficulty in assigning orthologous S. ratti transcripts to C. elegans ASP-5 and ASP-6 based on our phylogenetic analysis (Cluster III discussion below), numbers 5 and 6 were not used.

It is further notable that, in this tree, the two representative of Crenarchaeota (A. pernix and S. solfataricus) do not comprise a sister group of the Euryarchaeota (the remaining archaeal species), but rather for am branch within the Euryarchaeal cluster (see discussion below).

The outcome demonstrated 7 interesting clusters (see discussion below) with notable differences between yeast species comparing hypoxic and normoxic conditions, and 2 clusters (6 and 8) with a very similar profile for the pair wise oxygen comparisons and yeast species.

Gene functional annotation analysis of these hits using DAVID bioinformatics resources [19] has revealed interesting functional clustering (see discussion).

One cluster left for discussion is the one containing the CXA, CXC, GXC, GXT and TXC contexts.

Section 'Results and discussions' discusses the clustering performance for these zones, and Section 'Conclusions' concludes the article.

We have also performed a more careful analysis of severing position with respect to the cofilin clusters (in the Discussion section), which supports our original conclusion that severing occurs primarily near the boundary of cofilin clusters and bare zones, but not deeper inside the clusters or in bare zones far from clusters.

The Blips collect topical stories from across the Web and present the headlines in discussion clusters like you'd see on Techmeme, but stories can also then be voted up the page like on Digg.

In addition, it includes worked examples and a discussion of clustering algorithms (Hierarchical clustering, K-means clustering, self-organizing map) and classification methods (genetic algorithms, support vector machines).

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