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The dendrograms were generated from similarity matrix data by cluster analysis using unweighted pair group method for arithmetic mean (UPGMA).
Fig. 4 Floristic relationships between 22 geographical localities of Taiwan (GLT) and 34 ecoregions in Asia were analyzed by cluster analysis, using simple nearest neighbor algorithm and Bray Curtis dissimilarity method.
Subgroups corresponding to different gene copy numbers were defined by eye and confirmed by cluster analysis (using R statistical software version 2.5.0), and are delineated by elliptical lines.
A tree was created by cluster analysis using UPGMA.
Subgroup classification was conducted by cluster analysis using MPI subscale scores at entry into the program.
A tree was created by cluster analysis using the unweighted pair-group method with arithmetic averages (UPGMA).
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The discriminative power of the 187-gene expression signature in normal and tumor samples was tested by clustering analysis using oligonucleotide gene expression data obtained from 19 completely independent datasets.
These gene lists were compared by clustering analysis using Pearson correlation as a similarity measurement.
Similar profiles of the fold changes over time were identified by clustering analysis using the Self Organizing Tree Algorithm and default parameters of MeV version 4.6.
All species were in the top tier of 86 active isolates as determined by clustering analysis using the complete data set.
Gene expression profile by clustering analysis using heatmap representation (see Additional file 3) allowed the detection of gene patterns among treatments (chilling, salinity and control) confirmed by individual gene transcription profiles (see Additional file 2).
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by cluster analysis having
by immunofluorescence analysis using
by cluster amplification using
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by deconvolution analysis using
by bootstrap analysis using
by qPCR analysis using
by immunoblot analysis using
by regression analysis using
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