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BMCBI
2005
87views more  BMCBI 2005»
14 years 10 months ago
Efficient decoding algorithms for generalized hidden Markov model gene finders
Background: The Generalized Hidden Markov Model (GHMM) has proven a useful framework for the task of computational gene prediction in eukaryotic genomes, due to its flexibility an...
William H. Majoros, Mihaela Pertea, Arthur L. Delc...
ICPR
2008
IEEE
15 years 11 months ago
On efficient Viterbi decoding for hidden semi-Markov models
We present algorithms for improved Viterbi decoding for the case of hidden semi-Markov models. By carefully constructing directed acyclic graphs, we pose the decoding problem as t...
Bonnie K. Ray, Jianying Hu, Ritendra Datta
IJCAI
2003
14 years 11 months ago
A General Model for Online Probabilistic Plan Recognition
We present a new general framework for online istic plan recognition called the Abstract Hidden Markov Memory Model (AHMEM). The l is an extension of the existing Abstract Hidden ...
Hung Hai Bui
BMCBI
2005
89views more  BMCBI 2005»
14 years 10 months ago
An empirical analysis of training protocols for probabilistic gene finders
Background: Generalized hidden Markov models (GHMMs) appear to be approaching acceptance as a de facto standard for state-of-the-art ab initio gene finding, as evidenced by the re...
William H. Majoros, Steven Salzberg
BMCBI
2005
114views more  BMCBI 2005»
14 years 10 months ago
A new decoding algorithm for hidden Markov models improves the prediction of the topology of all-beta membrane proteins
Background: Structure prediction of membrane proteins is still a challenging computational problem. Hidden Markov models (HMM) have been successfully applied to the problem of pre...
Piero Fariselli, Pier Luigi Martelli, Rita Casadio