Uncovering Gene Regulatory Networks from DNA-microarray Data for Escherichia coli by Using A Neural Network Approach

Cells regulate their gene expression patterns in response to changes in environmental and physiological conditions This process of transcriptional regulation is carried out through a complex network of highly-interacted regulatory components whose properly inference necessitates employment of computational methodologies based on a global, genome-wide scale using ideas from system identification. Using a neural network approach, we demonstrated that this complex network of co-regulated genes can be described by only a few number of transcriptional regulators. We also examined the capability of this neural network approach in determining dynamics of multiple transcription factor activities, which can be considered as regulatory signals, using only DNA microarray data. We applied this approach to the regulatory network of Escherichia coli bacterium during carbon source transition from glucose to acetate. Key results from this analysis were either consistent with physiology or verified by using independent measurements..

Uncovering Gene Regulatory Networks from DNA-microarray Data for Escherichia coli by Using A Neural Network Approach Keywords:

Regulatory network , E. coli , Transcription factor , Neural network , Regulation