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Context-specific transcriptional regulatory network inference from global gene expression maps using double two-way t-tests

Context-specific transcriptional regulatory network inference from global gene expression maps using double two-way t-tests

This video was recorded at 6th International Workshop on Machine Learning in Systems Biology (MLSB), Basel 2012. Motivation: Transcriptional regulatory network inference methods have been studied for years. Most of them relie on complex mathematical and algorithmic concepts, making them hard to adapt, re- implement or integrate with other methods. To address this problem, we introduce a novel method based on a minimal statistical model for observing transcriptional regulatory interactions in noisy expression data, which is conceptually simple, easy to implement and integrate in any statistical software environment, and equally well performing as existing methods. Results: We developed a method to infer regulatory interactions based on a model where transcription factors (TFs) and their... Show More
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