Publication Date:
2020
Short description:
Bayesian learning of multiple essential graphs / La Rocca, L., Castelletti, F., Peluso, S., Stingo, F.C., Consonni, G. - In: Book of Short Papers SIS 2020 / [a cura di] Pollice, Alessio; Salvati, Nicola; Schirripa Spagnolo, Francesco. - [s.l] : Pearson, 2020. - ISBN 9788891910776. - pp. 447-452
abstract:
Structural learning of graphical models is a well-established approach to the identification of complex dependencies in biological networks. We here present a Bayesian methodology for learning directed networks from observational data when distinct subgroups of a population are observed.
Iris type:
Capitolo/Saggio
Keywords:
Markov equivalence, Markov random field, Objective Bayes
List of contributors:
La Rocca, Luca; Castelletti, Federico; Peluso, Stefano; Stingo, Francesco Claudio; Consonni, Guido
Book title:
Book of Short Papers SIS 2020