Sentence examples for by multivariate data analysis from inspiring English sources
Untargeted GCMS based metabolomics was used to analyse the constituents of the different growth media, followed by multivariate data analysis.
This research focusses on the development of a non-destructive characterization methodology of Islamic paper using NIR spectroscopy accompanied by multivariate data analysis.
Serum samples were analyzed using gas chromatography-mass spectrometry (GC MS) followed by multivariate data analysis to classify samples and determine if such treatments can help revert obesity related metabolic changes back to normal status.
NMR-based urine analysis followed by multivariate data analysis (metabonomics) identifies efficiently differences between toxic and non-toxic compounds; but in most cases multiple administrations of the test compound are necessary.
By multivariate data analysis, we could show that STAT3 expression and activity constitutes an independent favourable prognostic marker for CRC.
The metabolic phenotype of the cloned pigs was compared with normal outbred pigs (n = 6) by multivariate data analysis, which revealed differences in the metabolic phenotypes.
Index E is compared with about 200 other molecular descriptors by applying multivariate data analysis.
Molecular descriptors were computed following the TOPological Substructural MOlecular DEsign (TOPS-MODE) approach and correlated with β-CD complex stability constants by linear multivariate data analysis.
We aimed to compare the regulatory effects of the combination with its 4 individual constituents to discover potential biomarkers that could predict the cardioprotection of the combined-therapy by using multivariate data analysis.
We also performed a multivariate data analysis by employing the algorithm known as Regularized Least Squares (RLS) [ 45].
The basic idea behind FDA is to express discrete observations arising from time series in the form of a function (to create functional data) that represents the entire measured function as a single observation, and then to draw modeling and/or prediction information from a collection of functional data by applying statistical concepts from multivariate data analysis.
