Transmembrane Topology and Signal Peptide Prediction Using Dynamic Bayesian Networks

Hidden Markov models (HMMs) have been successfully applied to the tasks of transmembrane protein topology prediction and signal peptide prediction. In this paper we expand upon this work by making use of the more powerful class of dynamic Bayesian networks (DBNs). Our model, Philius, is inspired by...

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Bibliographic Details
Main Authors: Reynolds, Sheila M., Käll, Lukas, Riffle, Michael E., Bilmes, Jeff A., Noble, William Stafford
Format: Artigo
Language:Inglês
Published: Public Library of Science 2008
Subjects:
Research Article
Online Access:https://ncbi.nlm.nih.gov/pmc/articles/PMC2570248/
https://ncbi.nlm.nih.gov/pubmed/18989393
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1371/journal.pcbi.1000213
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