ArticleElectronic journal of statistics2016
Estimation of multiple networks in Gaussian mixture models.
Article in Electronic journal of statistics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
13 citing papers in PubMed.
- Network-based hierarchical heterogeneity analysis and applications to cancer omics data.Science China. Mathematics · 2026Article
- Robust Heterogeneity Adjustment for Gaussian Graphical Model With Latent Variables.Statistics in medicine · 2026Article
- LtransHeteroGGM: local transfer learning for Gaussian graphical model-based heterogeneity analysis.Bioinformatics (Oxford, England) · 2026Article
- Simultaneous clustering and estimation of networks in multiple graphical models.Biostatistics (Oxford, England) · 2025Article
- Subgroup Analysis of Differential Networks with Latent Variables.Statistics and computing · 2025Article
- AJGM: joint learning of heterogeneous gene networks with adaptive graphical model.Bioinformatics (Oxford, England) · 2025Article
- Estimation of multiple networks with common structures in heterogeneous subgroups.Journal of multivariate analysis · 2024Article
- Simultaneous cluster structure learning and estimation of heterogeneous graphs for matrix-variate fMRI data.Biometrics · 2023Article
- Inferring cell diversity in single cell data using consortium-scale epigenetic data as a biological anchor for cell identity.Nucleic acids research · 2023Article
- Penalized model-based clustering of fMRI data.Biostatistics (Oxford, England) · 2022Article
- Article
- Combining heterogeneous subgroups with graph-structured variable selection priors for Cox regression.BMC bioinformatics · 2021Article
- Simultaneous Clustering and Estimation of Heterogeneous Graphical Models.Journal of machine learning research : JMLR · 2018Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
We aim to estimate multiple networks in the presence of sample heterogeneity, where the independent samples (i.e. observations) may come from different and unknown populations or distributions. Specifically, we consider penalized estimation of multiple precision matrices in the framework of a Gaussian mixture model. A major innovation is to take advantage of the commonalities across the multiple precision matrices through possibly nonconvex fusion regularization, which for example makes it possible to achieve simultaneous discovery of unknown disease subtypes and detection of differential gene (dys)regulations in functional genomics. We embed in the EM algorithm one of two recently proposed methods for estimating multiple precision matrices in Gaussian graphical models. We demonstrate the feasibility and potential usefulness of the proposed methods in an application to glioblastoma subtype discovery and differential gene network analysis with a microarray gene expression data set. We also conduct realistic simulation studies to evaluate and compare the performance of various methods.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.