Sparse canonical correlation analysis for identifying, connecting and completing gene-expression networks [PDF]
BMC Bioinformatics, 2009 Background We generalized penalized canonical correlation analysis for analyzing microarray gene-expression measurements for checking completeness of known metabolic pathways and identifying candidate genes for incorporation in the pathway.
Zwinderman Aeilko H, Waaijenborg Sandra
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Sparse multivariate measures of similarity between intra-modal neuroimaging datasets [PDF]
Frontiers in Neuroscience, 2015 An increasing number of neuroimaging studies are now based on either combining more than one data modality (inter-modal) or combining more than one measurement from the same modality (intra-modal).
Maria J. Rosa +12 more
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Sparse tensor canonical correlation analysis for micro-expression recognition
Neurocomputing, 2016 A micro-expression is considered a fast facial movement that indicates genuine emotions and thus provides a cue for deception detection. Due to its promising applications in various fields, psychologists and computer scientists, particularly those focus on computer vision and pattern recognition, have shown interest and conducted research on this topic.
Sujing Wang +4 more
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IEEE AccessAttributed networks are prevalent in the current information infrastructure, where node attributes enhance knowledge discovery. Anomaly detection in attributed networks is gaining attention for its potential uses in cybersecurity, finance, and healthcare.
Wasim Khan +8 more
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Large-Scale Sparse Kernel Canonical Correlation Analysis.
, 2019 Peer ...
Rousu Juho, Uurtio Viivi, Bhadra Sahely
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Blunted niacin skin flushing response with subtype-specific clinical associations in adolescent bipolar disorder [PDF]
BMC PsychiatryBackground Bipolar disorder (BD) typically emerges during adolescence and is associated with substantial functional impairment, but objective physiological markers are scarce.
Jinxin He +13 more
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Preference Matrix Guided Sparse Canonical Correlation Analysis for Genetic Study of Quantitative Traits in Alzheimer's Disease. [PDF]
Proceedings (IEEE Int Conf Bioinformatics Biomed), 2022 Investigating the relationship between genetic variation and phenotypic traits is a key issue in quantitative genetics. Specifically for Alzheimer’s disease, the association between genetic markers and quantitative traits remains vague while, once ...
Sha J +12 more
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Preference matrix guided sparse canonical correlation analysis for mining brain imaging genetic associations in Alzheimer's disease. [PDF]
Methods, 2023 Investigating the relationship between genetic variation and phenotypic traits is a key issue in quantitative genetics. Specifically for Alzheimer's disease, the association between genetic markers and quantitative traits remains vague while, once ...
Sha J +13 more
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Sparse multiway canonical correlation analysis for multimodal stroke recovery data
Biometrical JournalAbstractConventional canonical correlation analysis (CCA) measures the association between two datasets and identifies relevant contributors. However, it encounters issues with execution and interpretation when the sample size is smaller than the number of variables or there are more than two datasets.
Subham Das +2 more
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Multi-Task Sparse Canonical Correlation Analysis with Application to Multi-Modal Brain Imaging Genetics. [PDF]
IEEE/ACM Trans Comput Biol Bioinform, 2021 Brain imaging genetics studies the genetic basis of brain structures and functionalities via integrating genotypic data such as single nucleotide polymorphisms (SNPs) and imaging quantitative traits (QTs). In this area, both multi-task learning (MTL) and
Du L +7 more
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