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Our previous single feature analysis discovered that an optimum ALogP was important for activity.
Single feature analysis provides a fast way to access the "good" or "bad" features for antiTB compounds.
Both rule analysis and single feature analysis imply NCO is a very important feature which is good for "active" and bad for "inactive".
The single feature analysis provides a lookup table (Additional file 1: Tables S1, S2, S3, and S4 and Figure 3) for general references of "good" or "bad" features.
This again is consistent with the results shown in our single feature analysis, where the phyletic retention measure was by far the most predictive feature.
However, whether combining multiple ECG features can improve the capability of defibrillation outcome prediction in comparison to single feature analysis is still uncertain.
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WWX contributed to microarray data analysis and performed single feature polymorphism analysis on microarray data.
Single Feature Polymorphisms (SFPs) analysis was performed as described in [ 18].
Therefore, single feature polymorphism (SFP) analysis [ 57] was performed using the Affymetrix® GeneChip data and an algorithm based on the Li-Wong model [ 58] combined with a modified probe level statistical method [ 59].
The features are based on the principle of static analysis, i. e., a single feature vector is extracted for each analysis segment.
Furthermore, an analysis of single feature polymorphisms in the Saltol region suggested that FL478 contained a <1 Mb DNA fragment from Pokkali at 10.6 11.5 Mb on chromosome 1, flanked by IR29 alleles (Kim et al. 2009).
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com