A stochastic context free grammar based framework for analysis of protein sequences

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Why is it important?

This paper describes the first description of amino acid patterns using an advanced grammar-based framework, i.e. stochastic context free grammar. Since grammar training does not rely on sequence homology and captures nested relationships, generated descriptors can capture patterns that are beyond the capability of HHM profiles that have been the reference in the field for more than 20 years. In addition, descriptors are human-readable and, hence, highlight biologically meaningful features. The citations suggest that this novel concept attracted interest amongst bioinformatics community even though the paper is quite theoretical.