Modeling promoter search by E. coli RNA polymerase: one-dimensional diffusion in a sequence-dependent energy landscape.

We present a biophysical model of promoter search by Escherichia coli RNA polymerase. We use an unconventional weight matrix derived from promoter strength data to extract the energy landscape common to a large set of known promoters. This exhibits a continuous strengthening of the binding energy when approaching the transcription start site from either side.

Translation initiation modeling and mutational analysis based on the 3(')-end of the Escherichia coli 16S rRNA sequence.

A model for the process of translation in gene expression is proposed. The model is based on the assumption that the ribosome decodes the mRNA sequences using consecutive subsequences of the 3(')-end of its 16S rRNA subunit. The biological consistency of the model is validated by successful detection of the Shine-Dalgarno signal and the start codon.

Modeling DNA-binding of Escherichia coli sigma70 exhibits a characteristic energy landscape around strong promoters.

We present a computational model of DNA-binding by sigma70 in Escherichia coli which allows us to extract the functional characteristics of the wider promoter environment. Our model is based on a measure for the binding energy of sigma70 to the DNA, which is derived from promoter strength data and used to build up a non-standard weight matrix. Opposed to conventional approaches, we apply the matrix to the environment of 3765 known promoters and consider the average matrix scores to extract the common features.