학술논문

Oncogenetic network estimation with disjunctive Bayesian networks
Document Type
article
Source
Computational and Systems Oncology, Vol 1, Iss 2, Pp n/a-n/a (2021)
Subject
Bayesian network
cancer progression
oncogenetic model
tumor phylogenetic
Neoplasms. Tumors. Oncology. Including cancer and carcinogens
RC254-282
Computer applications to medicine. Medical informatics
R858-859.7
Language
English
ISSN
2689-9655
Abstract
Abstract Motivation: Cancer is the process of accumulating genetic alterations that confer selective advantages to tumor cells. The order in which aberrations occur is not arbitrary, and inferring the order of events is challenging due to the lack of longitudinal samples from tumors. Moreover, a network model of oncogenesis should capture biological facts such as distinct progression trajectories of cancer subtypes and patterns of mutual exclusivity of alterations in the same pathways. In this paper, we present the disjunctive Bayesian network (DBN), a novel oncogenetic model with a phylogenetic interpretation. DBN is expressive enough to capture cancer subtypes' trajectories and mutually exclusive relations between alterations from unstratified data. Results: In cases where the number of studied alterations is small (