Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

Joint sparse canonical correlation analysis for detecting differential imaging genetics modules.

Bioinformatics (Oxford, England) - 15 Nov 2016

Fang Jian, Lin Dongdong, Schulz S Charles, Xu Zongben, Calhoun Vince D, Wang Yu-Ping

Abstract excerpt

MOTIVATION: Imaging genetics combines brain imaging and genetic information to identify the relationships between genetic variants and brain activities. When the data samples belong to different classes (e.g. disease status), the relationships may exhibit class-specific patterns that can be used to facilitate the understanding of a disease. Conventional approaches often perform separate analysis on each class and...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Brain
Share to Brain Mapping
Share to Genetic Variation

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Magnetic Resonance Imaging

Share to Polymorphism, Single Nucleotide

Share to Schizophrenia

Source

Open in PubMed Open full text

Identifiers

PMID: 27466625
DOI: 10.1093/bioinformatics/btw485
PMCID: PMC5181564

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 6 Sept 2026. Manifest publication-graph-cohort-2026-09-06.1.

Source receipt: pubmed, retrieved 6 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Joint sparse canonical correlation analysis for detecting differential imaging genetics modules.PMID 27466625Read ↗

Detecting genetic associations with brain imaging phenotypes in Alzheimer's disease via a novel structured SCCA approach.Semantic proximity Read ↗

Identifying Biomarkers of Alzheimer's Disease via a Novel Structured Sparse Canonical Correlation Analysis Approach.Semantic proximity Read ↗

Multi-Task Learning and Sparse Discriminant Canonical Correlation Analysis for Identification of Diagnosis-Specific Genotype-Phenotype Association.Semantic proximity Read ↗

Identifying Associations Between Brain Imaging Phenotypes and Genetic Factors via A Novel Structured SCCA Approach.Semantic proximity Read ↗

A novel structure-aware sparse learning algorithm for brain imaging genetics.Semantic proximity Read ↗

Sparse representation based biomarker selection for schizophrenia with integrated analysis of fMRI and SNPs.Semantic proximity Read ↗

Transcriptome-guided amyloid imaging genetic analysis via a novel structured sparse learning algorithm.Semantic proximity Read ↗

Mining Outcome-relevant Brain Imaging Genetic Associations via Three-way Sparse Canonical Correlation Analysis in Alzheimer's Disease.Semantic proximity Read ↗

Integrating Multimodal Neuroimaging and Genetics: A Structurally-Linked Sparse Canonical Correlation Analysis Approach.Semantic proximity Read ↗

Correspondence between fMRI and SNP data by group sparse canonical correlation analysis.Semantic proximity Read ↗

Pattern Discovery in Brain Imaging Genetics via SCCA Modeling with a Generic Non-convex Penalty.Semantic proximity Read ↗

Multimodal Imaging Genetic Analysis of Schizophrenia Based on Sparse Representation and Dictionary LearningSemantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.