Results 91 to 100 of about 689,927 (311)
Common Functional Principal Components [PDF]
Functional principal component analysis (FPCA) based on the Karhunen-Lo`eve decomposition has been successfully applied in many applications, mainly for one sample problems.
Michal Benko +2 more
core
Implementation of a local principal curves algorithm for neutrino interaction reconstruction in a liquid argon volume [PDF]
, 2014 A local principal curve algorithm has been implemented in three dimensions for automated track and shower reconstruction of neutrino interactions in a liquid argon time projection chamber.
B. Morgan +24 more
core +1 more source
gdpc: An R Package for Generalized Dynamic Principal Components
Journal of Statistical Software, 2020 gdpc is an R package for the computation of the generalized dynamic principal components proposed in Peña and Yohai (2016). In this paper, we briefly introduce the problem of dynamical principal components, propose a solution based on a reconstruction ...
Daniel Peña +2 more
doaj +1 more source
The ubiquitin ligase RNF115 is required for the clearance of damaged lysosomes
FEBS Letters, EarlyView.Upon lysosomal rupture, an E3 ubiquitin ligase RNF115 translocates from the cytosol to the damaged lysosomal membrane. Moreover, RNF115 depletion impairs the clearance of damaged lysosomes, identifying it as a key regulator of lysosomal quality control.
Sae Nakanaga +3 more
wiley +1 more source
Robust sparse principal component analysis. [PDF]
A method for principal component analysis is proposed that is sparse and robust at the same time. The sparsity delivers principal components that have loadings on a small number of variables, making them easier to interpret.
Croux, Christophe +2 more
core
Using Principal Components Analysis in Program Evaluation: Some Practical Considerations
Journal of MultiDisciplinary Evaluation, 2006 Principal Components Analysis (PCA) is widely used by behavioral science researchers to assess the dimensional structure of data and for data reduction purposes.
J. Thomas Kellow
doaj +1 more source
Integrated Principal Components Analysis
J. Mach. Learn. Res., 2018 Data integration, or the strategic analysis of multiple sources of data simultaneously, can often lead to discoveries that may be hidden in individualistic analyses of a single data source. We develop a new unsupervised data integration method named Integrated Principal Components Analysis (iPCA), which is a model-based generalization of PCA and serves
Tiffany M. Tang, Genevera I. Allen
openaire +4 more sources
FEBS Letters, EarlyView.Plasma membranes contain dynamic nanoscale domains that organize lipids and receptors. Because viruses operate at similar scales, this architecture shapes early infection steps, including attachment, receptor engagement, and entry. Using influenza A virus and HIV‐1 as examples, we highlight how receptor nanoclusters, multivalent glycan interactions ...
Jan Schlegel, Christian Sieben
wiley +1 more source
Image encoding by independent principal components
, 2010 The encoding of images by semantic entities is still an unresolved task. This paper proposes the encoding of images by only a few important components or image primitives. Classically, this can be done by the Principal Component Analysis (PCA). Recently,
Brause, Rüdiger W., Arlt, Björn
core
FEBS Letters, EarlyView.Embryo‐like structures (stembryos) are an innovative tool, but they are hindered by experimental variability and limited developmental potential. DNA methylation is crucial for mammalian development, but its status in stembryo models is poorly characterized.
Sara Canil +4 more
wiley +1 more source