Mimosa: Mixture model of co-expression to detect modulators of regulatory interaction

TitleMimosa: Mixture model of co-expression to detect modulators of regulatory interaction
Publication TypeJournal Articles
Year of Publication2010
AuthorsHansen M, Everett L, Singh L, Hannenhalli S
JournalAlgorithms for Molecular BiologyAlgorithms for Molecular Biology
Volume5
Type of Article10.1186/1748-7188-5-4
ISBN Number1748-7188
Abstract

Functionally related genes tend to be correlated in their expression patterns across multiple conditions and/or tissue-types. Thus co-expression networks are often used to investigate functional groups of genes. In particular, when one of the genes is a transcription factor (TF), the co-expression-based interaction is interpreted, with caution, as a direct regulatory interaction. However, any particular TF, and more importantly, any particular regulatory interaction, is likely to be active only in a subset of experimental conditions. Moreover, the subset of expression samples where the regulatory interaction holds may be marked by presence or absence of a modifier gene, such as an enzyme that post-translationally modifies the TF. Such subtlety of regulatory interactions is overlooked when one computes an overall expression correlation.