Results 31 to 40 of about 24,058,587 (288)
Using canonical correlation analysis to discover genetic regulatory variants. [PDF]
PLoS ONE, 2010 Discovering genetic associations between genetic markers and gene expression levels can provide insight into gene regulation and, potentially, mechanisms of disease.
Melissa G Naylor +4 more
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Scalable multi-label canonical correlation analysis for cross-modal retrieval [PDF]
, 2023 Multi-label canonical correlation analysis (ml-CCA) has been developed for cross-modal retrieval. However, the computation of ml-CCA involves dense matrices eigendecomposition, which can be computationally expensive.
Zhao, Guoying, Shu, Xin
core +1 more source
Canonical correlation analysis for gene-based pleiotropy discovery.
PLoS Computational Biology, 2014 Genome-wide association studies have identified a wealth of genetic variants involved in complex traits and multifactorial diseases. There is now considerable interest in testing variants for association with multiple phenotypes (pleiotropy) and for ...
Jose A Seoane +4 more
doaj +1 more source
Nonparametric Canonical Correlation Analysis
CoRR, 2015 Canonical correlation analysis (CCA) is a classical representation learning technique for finding correlated variables in multi-view data. Several nonlinear extensions of the original linear CCA have been proposed, including kernel and deep neural network methods. These approaches seek maximally correlated projections among families of functions, which
Tomer Michaeli +2 more
openaire +4 more sources
Adversarial Canonical Correlation Analysis
CoRR, 2020 Canonical Correlation Analysis (CCA) is a statistical technique used to extract common information from multiple data sources or views. It has been used in various representation learning problems, such as dimensionality reduction, word embedding, and clustering.
openaire +3 more sources
ANALYSIS OF STUDENT PERFORMANCE BASED ON CANONICAL CORRELATION ANALYSIS
Компютерні системи та інформаційні технологіїThe article examines the application of Canonical Correlation Analysis (CCA) to investigate the relationships between student performance outcomes across different groups of disciplines.
Катерина БЕРЕЗЬКА +3 more
doaj +1 more source
Associating Images with Sentences Using Recurrent Canonical Correlation Analysis
Applied Sciences, 2020 Associating images with sentences has drawn much attention recently. Existing methods commonly represent an image by indistinctively describing all its contents in an one-time static way, which ignores two facts that (1) the association analysis can only
Yawen Guo, Hui Yuan, Kun Zhang
doaj +1 more source
Solving the SSVEP Paradigm Using the Nonlinear Canonical Correlation Analysis Approach
Sensors, 2021 This paper presents the implementation of nonlinear canonical correlation analysis (NLCCA) approach to detect steady-state visual evoked potentials (SSVEP) quickly.
Danni Rodrigo De la Cruz-Guevara +2 more
doaj +1 more source
From mice to humans—divergent strategies for intestinal homeostasis and regeneration
FEBS Letters, EarlyView.Recent advances such as organoid genome editing, xenotransplantation, imaging, and whole‐genome sequencing have enabled direct studies of human intestinal stem cells (ISCs). These studies reveal species‐specific features, including slower ISC proliferation, distinct injury responses, slower somatic mutation accumulation in humans, and an inverse ...
Keiko Ishikawa +2 more
wiley +1 more source
Reconstructing enzyme evolution by protein engineering
FEBS Letters, EarlyView.Natural enzyme evolution can be retraced by protein engineering methods such as directed evolution, rational design, and ancestral sequence reconstruction. These approaches reveal how enzymes emerged from ligand‐binding scaffolds, developed varying substrate preferences, formed oligomeric complexes, adapted to environmental changes, and evolved novel ...
Lukas Drexler +2 more
wiley +1 more source