A multi-modal neural network using raw promoter DNA and transcription factor expression predicts yeast stress-response gene expression with 79.5% accuracy, and its in-silico MSN2/4 knockout predictions correlate with real microarray data (Spearman 0.486).
Towards reconstruction of gene networks from expression data by supervised learning
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A multi-modal neural network for learning cis and trans regulation of stress response in yeast
A multi-modal neural network using raw promoter DNA and transcription factor expression predicts yeast stress-response gene expression with 79.5% accuracy, and its in-silico MSN2/4 knockout predictions correlate with real microarray data (Spearman 0.486).