Maximum entropy modeling of short sequence motifs with applications to RNA splicing signals

摘要

We propose a framework for modeling sequence motifs based on the Maximum Entropy principle (MEP).We recommend approximating short sequence motif distributions with the Maximum Entropy Distribution (MED) consistent with low-order marginal constraints estimated from available data, which may include dependencies between non-adjacent as well as adjacent positions.Finally, we suggest mechanistically-motivated ways of comparing models.