Promoter Strength Prediction Based on Occurrence Frequencies of Consensus Patterns

A training sample of 14 sequences of E. coli, each 70 or 69 base pairs long, with their (relative) promoter strengths given by Deuschle et al. (1986, EMBO J.5, 2987-2994), is used to find a relation between the occurrence frequencies of the two consensus patterns and the promoter strength. The approach is restricted to an analysis of purine and pyrimidine organization using the theory of stationary alternate Markov chains of first order. r, it is shown, both empirically by regression analysis, and by a Markov-chain-oriented statistical analysis, that the difference of occurrence frequencies and the determinant of transition matrix, which was introduced in a previous paper (Recknagel et al., 1993, J. theor. Biol.162 , 75-80), are equivalent measures with respect to the task of promoter strength prediction. irical regression equation is given that allows the promoter strength to be forecast from the occurrence frequencies of the canonical hexamers in the consensus boxes. Three E. coli promoters of an examination sample, separated from the training sample, are classified this way, in agreement with the experimental findings.