Approaches to defining common and dissociable neurobiological deficits associated with psychopathology in youth
Psychiatric disorders show high rates of comorbidity and nonspecificity of presenting clinical
symptoms, while demonstrating substantial heterogeneity within diagnostic categories …
symptoms, while demonstrating substantial heterogeneity within diagnostic categories …
Multimodal MRI assessment for first episode psychosis: A major change in the thalamus and an efficient stratification of a subgroup
Multi‐institutional brain imaging studies have emerged to resolve conflicting results among
individual studies. However, adjusting multiple variables at the technical and cohort levels is …
individual studies. However, adjusting multiple variables at the technical and cohort levels is …
Integrative factor regression and its inference for multimodal data analysis
Multimodal data, where different types of data are collected from the same subjects, are fast
emerging in a large variety of scientific applications. Factor analysis is commonly used in …
emerging in a large variety of scientific applications. Factor analysis is commonly used in …
Generalized integrative principal component analysis for multi-type data with block-wise missing structure
High-dimensional multi-source data are encountered in many fields. Despite recent
developments on the integrative dimension reduction of such data, most existing methods …
developments on the integrative dimension reduction of such data, most existing methods …
Integrative factorization of bidimensionally linked matrices
Advances in molecular “omics” technologies have motivated new methodologies for the
integration of multiple sources of high-content biomedical data. However, most statistical …
integration of multiple sources of high-content biomedical data. However, most statistical …
sjive: Supervised joint and individual variation explained
EF Palzer, CH Wendt, RP Bowler, CP Hersh… - … statistics & data analysis, 2022 - Elsevier
Analyzing multi-source data, which are multiple views of data on the same subjects, has
become increasingly common in molecular biomedical research. Recent methods have …
become increasingly common in molecular biomedical research. Recent methods have …
[HTML][HTML] Bidimensional linked matrix factorization for pan-omics pan-cancer analysis
Several modern applications require the integration of multiple large data matrices that have
shared rows and/or columns. For example, cancer studies that integrate multiple omics …
shared rows and/or columns. For example, cancer studies that integrate multiple omics …
Hierarchical nuclear norm penalization for multi‐view data integration
The prevalence of data collected on the same set of samples from multiple sources (ie, multi‐
view data) has prompted significant development of data integration methods based on low …
view data) has prompted significant development of data integration methods based on low …
Sparse generalized eigenvalue problem with application to canonical correlation analysis for integrative analysis of methylation and gene expression data
We present a method for individual and integrative analysis of high dimension, low sample
size data that capitalizes on the recurring theme in multivariate analysis of projecting higher …
size data that capitalizes on the recurring theme in multivariate analysis of projecting higher …
Joint association and classification analysis of multi‐view data
Y Zhang, I Gaynanova - Biometrics, 2022 - Wiley Online Library
Multi‐view data, which is matched sets of measurements on the same subjects, have
become increasingly common with advances in multi‐omics technology. Often, it is of …
become increasingly common with advances in multi‐omics technology. Often, it is of …