A graphical chain model for inferring regulatory system networks from gene expression profiles

DOI10.1016/j.stamet.2005.08.004zbMath1248.62205OpenAlexW2028266503MaRDI QIDQ713675

Hiroyuki Toh, Katsuhisa Horimoto, Shigeru Saito, Sachiyo Aburatani

Publication date: 19 October 2012

Published in: Statistical Methodology (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.stamet.2005.08.004

zbMATH Keywords

cell cyclescovariance selectiongene expression profilegraphical Gaussian model

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Applications of statistics to biology and medical sciences; meta analysis (62P10) Applications of graph theory (05C90) Biochemistry, molecular biology (92C40) Cell biology (92C37) Genetics and epigenetics (92D10)

Uses Software

• MIM
• ASIAN

Cites Work

• Deduction of a gene regulatory relationship framework from gene expression data by the application of graphical Gaussian modeling
• Gaussian Markov distributions over finite graphs
• Markov fields and log-linear interaction models for contingency tables
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