Sentence examples for each cluster were analyzed from inspiring English sources
Sequence similarities among these Puf proteins in each cluster were analyzed and categorized (Fig. 2B).
The genes of each cluster were analyzed in search of regulatory elements within their promoter region.
Plant unigenes in each cluster were analyzed with the KEGG Automatic Annotation Server (KAAS) [ 110] to detect KEGG Orthologs (KO).
Upstream regions of genes present in each cluster were analyzed for de novo patterns using 3 pattern-finding algorithms: Multiple EM for Motif Elicitation (MEME) [ 70]; AlignACE [ 71] and Finding Informative Regulatory Elements (FIRE) algorithm [ 17].
This does not, however, affect the results as each cluster is analyzed by the types of innovations independently of each other.
Then, each cluster is analyzed by experts and labeled with the normal state or one of the considered faults as in the classification tree.
Each cluster was analyzed using a sliding window to locate the most likely cleavage site, defined as the position where the window contains the most EST/cDNA ends.
The genes most significantly contributing to each sample cluster were analyzed for their participation in the pathways contained both in GenMAPP [ 32], and GO (Tables 2 and 3).
Patterns of nucleotide variation in each gene cluster were analyzed using conventional approaches of molecular population genetics (Nei and Gojobori 1986; Nei 1987; Hey and Wakeley 1997).
Genes identified to be present in the same cluster were analyzed for overrepresented Gene Ontology Biological Process (GO-BP) terms.
