A method for probabilistic mapping between protein structure and function taxonomies through cross training

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Abstract
Prediction of function of proteins on the basis of structure and vice versa is a partially solved problem, largely in the domain of biophysics and biochemistry. This underlies the need of computational and bioinformatics approach to solve the problem. Large and organized latent knowledge on protein classification exists in the form of independently created protein classification databases. By creating probabilistic maps between classes of structural classification databases (e.g. SCOP 1) and classes of functional classification databases (e.g. PROSITE 2), structure and function of proteins could be probabilistically related.