Results 1 to 10 of about 14,354 (105)

Multi-Omics Data Fusion for Cancer Molecular Subtyping Using Sparse Canonical Correlation Analysis [PDF]

Frontiers in Genetics, 2021
It is now clear that major malignancies are heterogeneous diseases associated with diverse molecular properties and clinical outcomes, posing a great challenge for more individualized therapy.
Lin Qi, Wei Wang, Tan Wu, Lina Zhu, Lingli He, Xin Wang, Xin Wang   +6 more
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Identifying Imaging Genetics Biomarkers of Alzheimer’s Disease by Multi-Task Sparse Canonical Correlation Analysis and Regression [PDF]

Frontiers in Genetics, 2021
Imaging genetics combines neuroimaging and genetics to assess the relationships between genetic variants and changes in brain structure and metabolism.
Fengchun Ke, Wei Kong, Shuaiqun Wang
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Multivariate association between brain function and eating disorders using sparse canonical correlation analysis. [PDF]

PLoS ONE, 2020
Eating disorder is highly associated with obesity and it is related to brain dysfunction as well. Still, the functional substrates of the brain associated with behavioral traits of eating disorder are underexplored.
Hyebin Lee, Bo-Yong Park, Kyoungseob Byeon, Ji Hye Won, Mansu Kim, Se-Hong Kim, Hyunjin Park   +6 more
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An Improved Fusion Paired Group Lasso Structured Sparse Canonical Correlation Analysis Based on Brain Imaging Genetics to Identify Biomarkers of Alzheimer’s Disease [PDF]

Frontiers in Aging Neuroscience, 2022
Brain imaging genetics can demonstrate the complicated relationship between genetic factors and the structure or function of the humankind brain. Therefore, it has become an important research topic and attracted more and more attention from scholars ...
Shuaiqun Wang, Xinqi Wu, Kai Wei, Wei Kong   +3 more
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Integrating Multimodal Neuroimaging and Genetics: A Structurally-Linked Sparse Canonical Correlation Analysis Approach [PDF]

IEEE Journal of Translational Engineering in Health and Medicine
Neuroimaging genetics represents a multivariate approach aimed at elucidating the intricate relationships between high-dimensional genetic variations and neuroimaging data. Predominantly, existing methodologies revolve around Sparse Canonical Correlation
Jiwon Chung, Sunghun Kim, Ji Hye Won, Hyunjin Park   +3 more
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Classifying breast cancer subtypes on multi-omics data via sparse canonical correlation analysis and deep learning [PDF]

BMC Bioinformatics
Background Classifying breast cancer subtypes is crucial for clinical diagnosis and treatment. However, the early symptoms of breast cancer may not be apparent.
Yiran Huang, Pingfan Zeng, Cheng Zhong
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Multimodal data fusion using sparse canonical correlation analysis and cooperative learning: a COVID-19 cohort study [PDF]

npj Digital Medicine
Through technological innovations, patient cohorts can be examined from multiple views with high-dimensional, multiscale biomedical data to classify clinical phenotypes and predict outcomes.
Ahmet Gorkem Er, Daisy Yi Ding, Berrin Er, Mertcan Uzun, Mehmet Cakmak, Christoph Sadee, Gamze Durhan, Mustafa Nasuh Ozmen, Mine Durusu Tanriover, Arzu Topeli, Yesim Aydin Son, Robert Tibshirani, Serhat Unal, Olivier Gevaert   +13 more
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Leveraging expression from multiple tissues using sparse canonical correlation analysis and aggregate tests improves the power of transcriptome-wide association studies. [PDF]

PLoS Genetics, 2021
Transcriptome-wide association studies (TWAS) test the association between traits and genetically predicted gene expression levels. The power of a TWAS depends in part on the strength of the correlation between a genetic predictor of gene expression and ...
Helian Feng, Nicholas Mancuso, Alexander Gusev, Arunabha Majumdar, Megan Major, Bogdan Pasaniuc, Peter Kraft   +6 more
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Clinical application of sparse canonical correlation analysis to detect genetic associations with cortical thickness in Alzheimer’s disease [PDF]

Frontiers in Neuroscience
IntroductionAlzheimer’s disease (AD) is a progressive neurodegenerative disease characterized by cerebral cortex atrophy. In this study, we used sparse canonical correlation analysis (SCCA) to identify associations between single nucleotide polymorphisms
Bo-Hyun Kim, Sang Won Seo, Sang Won Seo, Sang Won Seo, Yu Hyun Park, JiHyun Kim, Hee Jin Kim, Hee Jin Kim, Hee Jin Kim, Hyemin Jang, Hyemin Jang, Hyemin Jang, Hyemin Jang, Jihwan Yun, Jihwan Yun, Jihwan Yun, Jihwan Yun, Mansu Kim, Jun Pyo Kim, Jun Pyo Kim, Jun Pyo Kim   +20 more
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Biomarker discovery by sparse canonical correlation analysis of complex clinical phenotypes of tuberculosis and malaria. [PDF]

PLoS Computational Biology, 2013
Biomarker discovery aims to find small subsets of relevant variables in 'omics data that correlate with the clinical syndromes of interest. Despite the fact that clinical phenotypes are usually characterized by a complex set of clinical parameters ...
Juho Rousu, Daniel D Agranoff, Olugbemiro Sodeinde, John Shawe-Taylor, Delmiro Fernandez-Reyes   +4 more
doaj   +2 more sources