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In order to get a measurement for genetic distance and thus to estimate the affinity between the diverse tumor entities, we applied the Cohen's Kappa Coefficient [ 21] to our binarized functional cancer map and clustered the distant relation matrix (figure 3).
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A transcription unit (TU) was defined as a consecutive genomic region where transcript sequences were mapped and clustered.
Interestingly, 76 major hot-spot regions were identified on eight LGs of genetic map in which more than two markers were mapped and clustered within 1 cM genetic distance.
From this, a total of 54 004 (75.2%) non-rice monocot FLcDNAs were mapped and clustered into 22 500 loci, from which 22 142 CDSs were predicted in the O. sativa genome.
Existing text feature extraction methods include filtration, fusion, mapping, and clustering method, which are briefly outlined below.
Only relatively recently have computers come close to this functionality with the introduction of data mining and machine learning techniques such as self organizing maps and clustering algorithms based on similarity metrics [ 75].
The observed errors were small, generally being below 10, 6, and 20% for load estimation, map resolution, and clustering accuracy, respectively.
Figure 5 Trained map and cluster detection.
Using a novel method to map and cluster chemical reactions, we have re-examined the chemistry of the ligases [Enzyme Commission (EC) Class 6] and their associated protein families in detail.
Figure 9 illustrates the heat map and cluster analysis of 503 conjugation-specific genes.
Heat Map and cluster analyses show that serum miRNA signatures can also be used to separate cancer patients and normal donors in most cases.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com