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In terms of the effect size measures, the proposed log ratio of mean method has higher sensitivity than the standardized mean difference method.
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NL-Means method has the second good result, unlike its performance on the other images.
Nonlocal means methods have been widely adopted as simple algorithms for image denoising, but they tend to overblur the image and sharpen the boundary with many texture details lost.
A new thematic map using the K-means clustering method has been built.
The k-means clustering method has been widely used in many fields [34] [39].
The k-means clustering method has been extensively used in analyses of gene [34], [35] or protein [36] expression data, protein 3D structural analysis [37], and image processing [38], [39].
In the mean time, indentation method has been well accepted as a simple and effective way to measure the mechanical properties of solid materials.
This may seem mean, but this method has a very strong effect.
Like any block-averaging or non-local means approach, our method has reduced performance near the edges of the image.
However, the target sequence and hybridization limitations of microarrays, combined with the availability of NGS-based RNAseq technologies, has meant that this method has been largely replaced in most systems.
The high PPV means that our method has a high proportion of correctly identified proteins in each predicted protein complex, which is consistent with the precision as analysed above.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com