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).
A bi-dimensional regression tree approach to the modeling of gene expression regulation
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
baseline 1
citation-polarity summary
fields
q-bio.GN 1years
2019 1verdicts
CONDITIONAL 1roles
baseline 1polarities
baseline 1representative citing papers
citing papers explorer
-
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).