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

A genetically informed, group FMRI connectivity modeling approach: application to schizophrenia.

IEEE transactions on bio-medical engineering - 1 Mar 2014

Liu Aiping, Chen Xiaohui, Wang Z Jane, Xu Qi, Appel-Cresswell Silke, McKeown Martin J

Abstract excerpt

While neuroimaging data can provide valuable phenotypic information to inform genetic studies, the opposite is also true: known genotypes can be used to inform brain connectivity patterns from fMRI data. Here, we propose a framework for genetically informed group brain connectivity modeling. Subjects are first stratified according to their genotypes, and then a group regularized regression model is employed for...

Read the complete abstract on PubMed

Topics

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

Share to Algorithms
Share to Brain Mapping

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Carrier Proteins

Share to Computer Simulation

Share to Intracellular Signaling Peptides and Proteins

Share to Magnetic Resonance Imaging

Share to Models, Neurological

Share to Schizophrenia

Source

Identifiers

PMID: 24557696
DOI: 10.1109/TBME.2013.2294151

Genes

DAOA

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

A genetically informed, group FMRI connectivity modeling approach: application to schizophrenia.PMID 24557696Read ↗

Functional neuroimaging and schizophrenia: a view towards effective connectivity modeling and polygenic risk.Semantic proximity Read ↗

Guided exploration of genomic risk for gray matter abnormalities in schizophrenia using parallel independent component analysis with reference.Semantic proximity Read ↗

Incremental predictive value of genetic risk and functional brain connectivity in determining antipsychotic response in schizophrenia.Semantic proximity Read ↗

Group ICA for Identifying Biomarkers in Schizophrenia: ‘Adaptive’ Networks via Spatially Constrained ICA Show More Sensitivity to Group Differences than Spatio-temporal RegressionSemantic proximity Read ↗

Seeking Optimal Region-Of-Interest (ROI) Single-Value Summary Measures for fMRI Studies in Imaging Genetics.Semantic proximity Read ↗

A pilot multivariate parallel ICA study to investigate differential linkage between neural networks and genetic profiles in schizophrenia.Semantic proximity Read ↗

A meta-analysis of fMRI studies in healthy relatives of patients with schizophrenia.Semantic proximity Read ↗

Decreased white matter FA values in the left inferior frontal gyrus is a possible intermediate phenotype of schizophrenia: evidences from a novel group strategy.Semantic proximity Read ↗

Task-based functional connectivity as an indicator of genetic liability to schizophrenia.Semantic proximity Read ↗

Extended Bayesian model averaging in generalized linear mixed models applied to schizophrenia family data.Semantic proximity Read ↗

A Bayesian group sparse multi-task regression model for imaging genetics.Semantic proximity Read ↗

Associations between polygenic risk for schizophrenia and brain function during probabilistic learning in healthy individuals.Semantic proximity Read ↗

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