Results 51 to 60 of about 415,661 (284)
Canonical correlation analysis of high-dimensional data with very small sample support [PDF]
, 2016 This paper is concerned with the analysis of correlation between two high-dimensional data sets when there are only few correlated signal components but the number of samples is very small, possibly much smaller than the dimensions of the data. In such a
Hasija, Tanuj +3 more
core +2 more sources
Molecular Oncology, EarlyView.Glioma cells mainly express the endothelin receptor EDNRB, while EDNRA is restricted to a perivascular tumor subpopulation. Endothelin signaling reduces glioma cell proliferation while promoting migration and a proneural‐to‐mesenchymal transition associated with poor prognosis. This pathway activates Ca2+, K+, ERK, and STAT3 signalings and is regulated
Donovan Pineau +36 more
wiley +1 more source
A Corrected Criterion for Selecting the Optimum Number of Principal Components
Austrian Journal of Statistics, 2016 Determining the optimum number of components to be retained is a key problem in principal component analysis (PCA). Besides the rule of thumb estimates there exist several sophisticated methods for automatically selecting the dimensionality of the data ...
Hannes Kazianka, Jürgen Pilz
doaj +1 more source
A Single Classifier Using Principal Components Vs Multi-Classifier System: In Landuse-LandCover Classification of WorldView-2 Sensor Data [PDF]
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2014 In remote sensing community, Principal Component Analysis (PCA) is widely utilized for dimensionality reduction in order to deal with high spectral-dimension data. However, dimensionality reduction through PCA results in loss of some spectral information.
L .N. Eeti +2 more
doaj +1 more source
Uncertainty-Aware Principal Component Analysis
, 2019 We present a technique to perform dimensionality reduction on data that is subject to uncertainty. Our method is a generalization of traditional principal component analysis (PCA) to multivariate probability distributions.
Deussen, Oliver +4 more
core +1 more source
Molecular Oncology, EarlyView.Pancreatic sensory neurons innervating healthy and PDAC tissue were retrogradely labeled and profiled by single‐cell RNA sequencing. Tumor‐associated innervation showed a dominant neurofilament‐positive subtype, altered mitochondrial gene signatures, and reduced non‐peptidergic neurons.
Elena Genova +14 more
wiley +1 more source
Molecular Oncology, EarlyView.Beyond its role in immune evasion, this study identified that CD47 drives tumor‐intrinsic signaling in non‐small cell lung cancer (NSCLC). Transcriptomic profiling and functional studies revealed that CD47 regulates cell adhesion, migration, and metastasis through an ERK–EMT signaling axis.
Asa P.Y. Lau +8 more
wiley +1 more source
Face Detection using Principal Component Analysis (PCA)
International Journal of Computer Applications, 2014 Face Detection makes it possible to use the facial images of a person to authenticate him into secure system, for criminal identification, for passport verification etc. It is done by Principal Component Analysis (PCA).Face images are projected onto a face space that encodes best variation among known face images.
Tarun Metta, Jatin Agarwal, Pushpak Dave
openaire +1 more source
KDM7A and KDM1A inhibition suppresses tumour promoting pathways in prostate cancer
Molecular Oncology, EarlyView.Treatment resistance is a major challenge for patients with advanced prostate cancer. This study examined an alternative approach to target the major prostate cancer‐promoting pathway by targeting epigenetic factors, whose levels are higher in tumours.
Jennie N Jeyapalan +16 more
wiley +1 more source
Remote SensingTimely detection of insect infestation (or other disturbance) in a forest is vital for an adequate response plan to be developed. To determine the status of an active infestation of southern pine beetle (Dendroctonus frontalis) in the Bienville National ...
Michael K. Crosby +6 more
doaj +1 more source