Variable-order Bayesian network: Difference between revisions

Content deleted Content added
m bypsas
Line 1:
'''Variable-order Bayesian network (VOBN)''' models provide an important extension of both the [[Bayesian network]] models and the [[variable -order Markov models]]. VOBN models are used in [[machine learning]] in general and have shown great potential in [[bioinformatics]] applications.<ref name="Ben-Gal">{{cite journal|last = Ben-Gal|first = I.|coauthors = Shani A., Gohr A., Grau J., Arviv S., Shmilovici A., Posch S. and Grosse I.|title = Identification of Transcription Factor Binding Sites with Variable-order Bayesian Networks|journal = Bioinformatics|volume = 21|issue = 11|date = 2005|pages = 2657-2666|url = http://bioinformatics.oxfordjournals.org/cgi/reprint/bti410?ijkey=KkxNhRdTSfvtvXY&keytype=ref}}</ref><ref name="Grau">{{cite journal|last = Grau|first = J.|coauthors = Ben-Gal I., Posch S., Grosse I.|title = VOMBAT: Prediction of Transcription Factor Binding Sites using Variable Order Bayesian Trees|journal = Nucleic Acids Research |volume = 34|date = 2006|pages = 529–533|url = http://www.eng.tau.ac.il/~bengal/VOMBAT.pdf}}</ref>
These models extend the widely-used [[position weight matrix]] (PWM) models, [[Markov model]]s, and Bayesian network (BN) models.