Predicting Binding of Transcriptional Regulators with a Two-way Latent Grouping Model
Samuel Kaski, Eerika Savia and Kai Puolamäki
In: 13th Annual International Conference on Intelligent Systems for Molecular Biology (ISMB 2005), 25-29 Jun 2005, Detroit, Michigan.
Binding of transcriptional regulators can be measured genome-wide to reveal regulatory networks. The measurements are noisy and expensive, however. We model existing binding data in order to predict binding for new factors or genes, assuming groups of genes and groups of transcription factors have similar binding patterns.
We model the binding patterns using recent ideas from collaborative
filtering and biclustering. A main difference from biclustering is
that we compute a Bayesian prediction using all possible clusterings.
|EPrint Type:||Conference or Workshop Item (Poster)|
|Project Keyword:||Project Keyword UNSPECIFIED|
|Subjects:||Theory & Algorithms|
|Deposited By:||Eerika Savia|
|Deposited On:||24 November 2005|