A pipeline to create predictive functional networks: application to the tumor progression of hepatocellular carcinoma

A pipeline to create predictive functional networks: application to the tumor progression of hepatocellular carcinoma

Abstract Background Integrating genome-wide gene expression patient profiles with regulatory knowledge is a challenging task because of the inherent heterogeneity, noise and incompleteness of biological data. From the computational side, several solvers for logic programs are able to perform extreme...

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Bibliographic Details
Main Authors: Maxime Folschette, Vincent Legagneux, Arnaud Poret, Lokmane Chebouba, Carito Guziolowski, Nathalie Théret
Format: Article
Language:English
Published: BMC 2020-01-01
Series:BMC Bioinformatics
Subjects:
Data and network integration
Discrete modeling
Hepatocellular carcinoma
Signaling and regulatory knowledge
KEGG
Online Access:https://doi.org/10.1186/s12859-019-3316-1

Internet

https://doi.org/10.1186/s12859-019-3316-1

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