Promoter-motif extraction from co-regulated genes and their relevance to co-expression using E. coli as a model

Gene expression varies due to the intrinsic stochasticity of transcription or as a reaction to external perturbations that generate cellular mutations. Co-regulation, co-expression and functional similarity of substances have been employed for indoctrinating the process of the transcriptional paradigm. The difficult process of analysing complicated proteomes and biological switches has been made easier by technical improvements, and microarray technology has flourished as a viable platform. Therefore, this research enables Microarray to cluster genes that are co-expressed and co-regulated into specific segments. Copious search algorithms have been employed to ascertain diacritic motifs or a combination of motifs that are performing regular expression, and their relevant information corresponding to the gene patterns is also documented. The associated genes co-expression and relevant cis-elements are further explored by engaging Escherichia coli as a model organism. Various clustering algorithms have also been used to generate classes of genes with similar expression profiles. A promoter database 'EcoPromDB' has been developed by referring RegulonDB database; this promoter database is freely available at and is divided into two sub-groups, depending upon the results of co-expression and co-regulation analyses.