Background: This paper describes techniques for accelerating the performance of the string set matching problem with particular emphasis on applications in computational proteomic...
Yoginder S. Dandass, Shane C. Burgess, Mark Lawren...
Background: There exist many segmentation techniques for genomic sequences, and the segmentations can also be based on many different biological features. We show how to evaluate ...
Hidden Markov models (HMMs) have been successfully applied to a variety of problems in molecular biology, ranging from alignment problems to gene nding and annotation. Alignment p...
In this work, a new learning paradigm called target selection is proposed, which can be used to test for associations between a single genetic variable and a multidimensional, qua...
Johannes Mohr, Sambu Seo, Imke Puis, Andreas Heinz...
Abstract. Hidden Markov models are traditionally decoded by the Viterbi algorithm which finds the highest probability state path in the model. In recent years, several limitations ...