Algorithms on strings, trees, and sequences: computer science and computational biology
Algorithms on strings, trees, and sequences: computer science and computational biology
A Generalized Hidden Markov Model for the Recognition of Human Genes in DNA
Proceedings of the Fourth International Conference on Intelligent Systems for Molecular Biology
The Conserved Exon Method for Gene Finding
Proceedings of the Eighth International Conference on Intelligent Systems for Molecular Biology
Domino tiling, gene recognition, and mice
Domino tiling, gene recognition, and mice
Comparative Methods for Gene Structure Prediction in Homologous Sequences
WABI '02 Proceedings of the Second International Workshop on Algorithms in Bioinformatics
Behavioral distance measurement using hidden markov models
RAID'06 Proceedings of the 9th international conference on Recent Advances in Intrusion Detection
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Hidden Markov models (HMMs) have been successfully applied to a variety of problems in molecular biology, ranging from alignment problems to gene finding and annotation. Alignment problems can be solved with pair HMMs, while gene finding programs rely on generalized HMMs in order to model exon lengths. In this paper we introduce the generalized pair HMM (GPHMM), which is an extension of both pair and generalized HMMs. We show how GPHMMs, in conjunction with approximate alignments, can be used for cross-species gene finding, and describe applications to DNA-cDNA and DNA-protein alignment. GPHMMs provide a unifying and probabilistically sound theory for modeling these problems.