univariate analysis
3 RESULTS
45-1 Ramsey Road, Shirley, NY 11967, USA, Shirley
Tel: +1 6316197922
Univariate analysis is very common in statistical analysis with only one variable involved. The analytic results are descriptive or inferential thus this analysis is widely used for the analysis of data collected from proteomics or metabolomics. Metabolomic data are usually multi-dimensional with the number of features (peaks metabolites) ranging from several dozen to hundreds or even thousands. The features of acquired data represent snapshots of global biochemical profiles of each organism. The majority of these features are expected to be within normal physiological range while some of the features may fluctuate dramatically due to the change of physiological conditions. Identifying... read more
Tel: +1 6316197922
Univariate analysis is very common in statistical analysis with only one variable involved. The analytic results are descriptive or inferential thus this analysis is widely used for the analysis of data collected from proteomics or metabolomics. Metabolomic data are usually multi-dimensional with the number of features (peaks metabolites) ranging from several dozen to hundreds or even thousands. The features of acquired data represent snapshots of global biochemical profiles of each organism. The majority of these features are expected to be within normal physiological range while some of the features may fluctuate dramatically due to the change of physiological conditions. Identifying... read more
45-1 Ramsey Road, Shirley, NY 11967, USA, Shirley
Tel: +1 6316197922
Univariate analysis is very common in statistical analysis with only one variable involved. The analytic results are descriptive or inferential thus this analysis is widely used for the analysis of data collected from proteomics or metabolomics. Metabolomic data are usually multi-dimensional with the number of features (peaks metabolites) ranging from several dozen to hundreds or even thousands. The features of acquired data represent snapshots of global biochemical profiles of each organism. The majority of these features are expected to be within normal physiological range while some of the features may fluctuate dramatically due to the change of physiological conditions. Identifying... read more
Tel: +1 6316197922
Univariate analysis is very common in statistical analysis with only one variable involved. The analytic results are descriptive or inferential thus this analysis is widely used for the analysis of data collected from proteomics or metabolomics. Metabolomic data are usually multi-dimensional with the number of features (peaks metabolites) ranging from several dozen to hundreds or even thousands. The features of acquired data represent snapshots of global biochemical profiles of each organism. The majority of these features are expected to be within normal physiological range while some of the features may fluctuate dramatically due to the change of physiological conditions. Identifying... read more
shirley, NY USA, Accord
Univariate analysis is very common in statistical analysis with only one variable involved. The analytic results are descriptive or inferential thus this analysis is widely used for the analysis of data collected from proteomics or metabolomics. Metabolomic data are usually multi-dimensional with the number of features (peaks metabolites) ranging from several dozen to hundreds or even thousands. The features of acquired data represent snapshots of global biochemical profiles of each organism. The majority of these features are expected to be within normal physiological range while some of the features may fluctuate dramatically due to the change of physiological conditions. Identifying... read more
Univariate analysis is very common in statistical analysis with only one variable involved. The analytic results are descriptive or inferential thus this analysis is widely used for the analysis of data collected from proteomics or metabolomics. Metabolomic data are usually multi-dimensional with the number of features (peaks metabolites) ranging from several dozen to hundreds or even thousands. The features of acquired data represent snapshots of global biochemical profiles of each organism. The majority of these features are expected to be within normal physiological range while some of the features may fluctuate dramatically due to the change of physiological conditions. Identifying... read more
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