M-BISON: Microarray-based integration of data sources using networks

Background: The accurate detection of differentially expressed (DE) genes has become a central task in microarray analysis. Unfortunately, the noise level and experimental variability of microarrays can be limiting. While a number of existing methods partially overcome these limitations by incorporating biological knowledge in the form of gene groups, these methods sacrifice gene-level resolution. This loss of precision can be inappropriate, especially if the desired output is a ranked list of individual genes. To address this shortcoming, we developed M-BISON (Microarray-Based Integration of data SOurces using Networks), a formal probabilistic model that integrates background biological knowledge with microarray data to predict individual DE genes. Results: M-BISON improves signal detection on a range of simulated data, particularly when using very noisy microarray data. We also applied the method to the task of predicting heat shockrelated differentially expressed genes in S. cerevi...

• Type: Journal
• Year: 2008
• Where: BMCBI
• Authors: Bernie J. Daigle Jr., Russ B. Altman
• Keywords: Biological Knowledge, BMCBI 2008, De Gene, Microarray Data