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The pre-image problem has to be solved during inference by most structuredoutput predictors. For string kernels, this problem corresponds to finding thestring associated to a given input. An algorithm capable of solving or findinggood approximations to this problem would have many applications incomputational biology and other fields. This work uses a recent result oncombinatorial optimization of linear predictors based on string kernels todevelop, for the pre-image, a low complexity upper bound valid for many stringkernels. This upper bound is used with success in a branch and bound searchingalgorithm. Applications and results in the discovery of druggable peptides arepresented and discussed.

On the String Kernel Pre-Image Problem with Applications in Drug Discovery