Results 81 to 90 of about 15,041 (261)
$\ell_0$-based Sparse Canonical Correlation Analysis
Canonical Correlation Analysis (CCA) models are powerful for studying the associations between two sets of variables. The canonically correlated representations, termed \textit{canonical variates} are widely used in unsupervised learning to analyze unlabeled multi-modal registered datasets.
Lindenbaum, Ofir +3 more
openaire +2 more sources
This study constructed the first spatiotemporal multi‐omics map of peach fruit and discovered a key candidate gene that synergistically regulates trichome development and drought tolerance through the jasmonic acid signaling pathway, providing insights into the coupling mechanism between development and stress resistance.
Zhixin Liu +9 more
wiley +1 more source
Minimax estimation in sparse canonical correlation analysis
Canonical correlation analysis is a widely used multivariate statistical technique for exploring the relation between two sets of variables. This paper considers the problem of estimating the leading canonical correlation directions in high-dimensional settings. Recently, under the assumption that the leading canonical correlation directions are sparse,
Gao, Chao +3 more
openaire +4 more sources
Corneal nerve regeneration is critical to corneal wound healing processes. The current study reveals a novel role of MG53 in promoting corneal nerve regeneration after alkali induced injury. Mechanistically, MG53 enters macrophages via its receptor, MPEG1, promotes MVP K63 ubiquitination, and triggers STAT6 induced repair‐related genes expression ...
Peng Chen +14 more
wiley +1 more source
Sparse Canonical Correlation Analysis
Large scale genomic studies of the association of gene expression with multiple phenotypic or genotypic measures may require the identification of complex multivariate relationships.
Parkhomenko, Elena
core +1 more source
As a neurodegenerative disease, Alzheimer’s disease (AD) has many symptoms, such as memory impairment, cognitive decline, and personality change. Image genetics is the correlation analysis between imageology and genetics, and image genetics research can ...
Tao Yang, GuangYu Wan, Xiong Zhou
doaj +1 more source
Structure-constrained sparse canonical correlation analysis with an application to microbiome data analysis. [PDF]
Motivated by studying the association between nutrient intake and human gut microbiome composition, we developed a method for structure-constrained sparse canonical correlation analysis (ssCCA) in a high-dimensional setting. ssCCA takes into account the phylogenetic relationships among bacteria, which provides important prior knowledge on evolutionary ...
Chen J +4 more
europepmc +4 more sources
Bone cancer pain and depression share a common origin: astrocytic A2‐to‐A1 transition in the posterior piriform cortex. This phenotypic shift disrupts the ATP–adenosine–A2AR–norepinephrine axis, simultaneously driving nociceptive and affective dysfunction.
Jiang‐Ping Liu +14 more
wiley +1 more source
Despite the widespread use of lesion-symptom mapping (LSM) techniques to study associations between location of brain damage and language deficits, the prediction of language deficits from lesion location remains a substantial challenge.
Melissa Thye, Daniel Mirman
doaj +1 more source
Integration of multidimensional splicing data and GWAS summary statistics for risk gene discovery.
A common strategy for the functional interpretation of genome-wide association study (GWAS) findings has been the integrative analysis of GWAS and expression data.
Ying Ji +5 more
doaj +1 more source

