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BMCBI
2005
87views more  BMCBI 2005»
13 years 4 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
14 years 6 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
13 years 6 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»
13 years 4 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»
13 years 4 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