Tailored graphical lasso for data integration in gene network reconstruction

Tailored graphical lasso for data integration in gene network reconstruction

Background: Identifying gene interactions is a topic of great importance in genomics, and approaches based on network models provide a powerful tool for studying these. Assuming a Gaussian graphical model, a gene association network may be estimated from multiomic data based on the non-zero entries...

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Bibliographic Details
Main Authors: Bergholtz, H. (Author), Borgan, Ø. (Author), Glad, I.K (Author), Lien, T.G (Author), Lingjærde, C. (Author)
Format: Article
Language:English
Published: BioMed Central Ltd 2021
Subjects:
algorithm
Algorithms
Cancer genomics
Clustering algorithms
Covariance matrix
Data integration
Gene networks
gene regulatory network
Gene Regulatory Networks
Genes
Genome
genomics
Genomics
Graphical lasso
Graphical lassos
High dimensional inference
High-dimensional inference
Integrative analysis
Inverse problems
Multiomic
Multiomics
Network models
normal distribution
Normal Distribution
protein analysis
Protein Interaction Maps
Protein-protein interaction networks
Protein–protein interaction networks
Proteins
Weighted graphical lasso
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