1.
Maximizing the Power of Principal-Component Analysis of Correlated Phenotypes in Genome-wide Association Studies
by Aschard, Hugues
American journal of human genetics, 2014, Vol.94 (5), p.662-676
2.
Use of Raman spectroscopy and chemometrics to distinguish blue ballpoint pen inks
by de Souza Lins Borba, Flávia
Forensic science international, 2015, Vol.249, p.73-82
3.
Comparison of discrete-point vs. dimensionality-reduction techniques for describing performance-related aspects of maximal vertical jumping
by Richter, Chris
Journal of biomechanics, 2014, Vol.47 (12), p.3012-3017
4.
Neonates with reduced neonatal lung function have systemic low-grade inflammation
by Chawes, Bo L.K., MD, PhD
Journal of allergy and clinical immunology, 2014, Vol.135 (6), p.1450-1456.e1
5.
Inflammatory endotypes of chronic rhinosinusitis based on cluster analysis of biomarkers
by Tomassen, Peter, MD
Journal of allergy and clinical immunology, 2016, Vol.137 (5), p.1449-1456.e4
6.
Selected statistical methods of data analysis for multivariate functional data
by Gorecki, Tomasz
Statistical papers (Berlin, Germany), 2016, Vol.59 (1), p.153-182
7.
Machine learning of the spatio-temporal characteristics of echocardiographic deformation curves for infarct classification
by Tabassian, Mahdi
The International Journal of Cardiovascular Imaging, 2017, Vol.33 (8), p.1159-1167
8.
Correlation structure and principal components in the global crude oil market
by Dai, Yue-Hua
Empirical economics, 2016, Vol.51 (4), p.1501-1519
9.
Sparse common component analysis for multiple high-dimensional datasets via noncentered principal component analysis
by Park, Heewon
Statistical papers (Berlin, Germany), 2018, Vol.61 (6), p.2283-2311
10.
Fast Principal-Component Analysis Reveals Convergent Evolution of ADH1B in Europe and East Asia
by Galinsky, Kevin J
American journal of human genetics, 2016, Vol.98 (3), p.456-472
11.
Unsupervised Discovery of Demixed, Low-Dimensional Neural Dynamics across Multiple Timescales through Tensor Component Analysis
by Williams, Alex H
Neuron (Cambridge, Mass.), 2018, Vol.98 (6), p.1099-1115.e8
12.
Metabolic profiling as a tool for revealing Saccharomyces interactions during wine fermentation
by Howell, Kate S
FEMS yeast research, 2006, Vol.6 (1), p.91-101
13.
Fast, reagentless and reliable screening of “white powders” during the bioterrorism hoaxes
by Włodarski, Maksymilian
Forensic science international, 2015, Vol.248, p.71-77
14.
On exploratory factor analysis: A review of recent evidence, an assessment of current practice, and recommendations for future use
by Gaskin, Cadeyrn J
International journal of nursing studies, 2014, Vol.51 (3), p.511-521
15.
Reconstructing Indian population history
by Reich, David
Nature, 2009, Vol.461 (7263), p.489-494
16.
Activation of camalexin biosynthesis in Arabidopsis thaliana in response to perception of bacterial lipopolysaccharides: a gene-to-metabolite study
by Beets, Caryn Ann
Planta, 2012, Vol.236 (1), p.261-272
17.
Temporal specification and bilaterality of human neocortical topographic gene expression
by Pletikos, Mihovil
Neuron (Cambridge, Mass.), 2014, Vol.81 (2), p.321-332
18.
A novel robust principal component analysis method for image and video processing
by Huan, Guoqiang
Applications of mathematics (Prague), 2016, Vol.61 (2), p.197-214
19.
Improved Ancestry Estimation for both Genotyping and Sequencing Data using Projection Procrustes Analysis and Genotype Imputation
by Wang, Chaolong
American journal of human genetics, 2015, Vol.96 (6), p.926-937
20.
Comparative Analysis of Principal Components Can be Misleading
by Uyeda, Josef C
Systematic biology, 2015, Vol.64 (4), p.677-689
