Inference of logic networks from insertion and expression data

Poster (2008)

Authors

J. de Ridder Netherlands Cancer Institute, Pattern Recognition and Bioinformatics -

M.J.T. Reinders Pattern Recognition and Bioinformatics -

L.F.A. Wessels Netherlands Cancer Institute, Pattern Recognition and Bioinformatics -

Research Group

Pattern Recognition and Bioinformatics () (TU Delft)

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http://resolver.tudelft.nl/uuid:91cd0c6c-f69b-48a9-9d63-2f331611cc2c

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Published Date

2008

Language

English

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Faculty

Electrical Engineering, Mathematics and Computer Science

Department

Intelligent Systems

Research Group

Pattern Recognition and Bioinformatics

Abstract

In this study, 43 tumors, that were induced by retroviral insertional mutagenesis, are profiled, resulting in a dataset for which both the initiating events (the viral integration sites) as well as the consequent expression profiles are available. We infer associations between insertion loci and gene expression profiles, while explicitly incorporating simple boolean logic, modelling multiple and parallel oncogenic pathways. We show that this results in the discovery of interesting causal associations between virally inserted loci and differentially expressed genes in tumorigenesis.