Skip to main content
Kent Academic Repository

The integration of heterogeneous biological data using Bayesian networks

McGarry, Ken and Morris, Nick and Freitas, Alex A. (2006) The integration of heterogeneous biological data using Bayesian networks. In: Ellis, Richard and Allen, Tony and Tuson, Andrew, eds. Applications and Innovations in Intelligent Systems XIV Proceedings of AI-2006, the Twenty-sixth SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence. Springer, pp. 44-57. ISBN 978-1-84628-665-0. E-ISBN 978-1-84628-666-7. (doi:10.1007/978-1-84628-666-7_4) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:14390)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided.
Official URL:
http://dx.doi.org/10.1007/978-1-84628-666-7_4

Abstract

Bayesian networks can provide a suitable framework for the integration of highly heterogeneous experimental data and domain knowledge from experts and ontologies. In addition, they can produce interpretable and understandable models for knowledge discovery within complex domains by providing knowledge of casual and other relationships in the data. We have developed a system using Bayesian Networks that enables domain experts to express their knowledge and integrate it with a variety of other sources such as protein-protein relationships and to cross-reference this against new knowledge discovered by the proteomics experiments. The underlying Bayesian mechanism enables a form of hypothesis testing and evaluation.

Item Type: Book section
DOI/Identification number: 10.1007/978-1-84628-666-7_4
Uncontrolled keywords: Markov Chain Monte Carlo; Bayesian Network; Markov Chain Monte Carlo Method; Conditional Probability Distribution; Conditional Probability Table
Subjects: Q Science > QA Mathematics (inc Computing science) > QA 76 Software, computer programming,
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing
Depositing User: Mark Wheadon
Date Deposited: 24 Nov 2008 18:03 UTC
Last Modified: 16 Nov 2021 09:52 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/14390 (The current URI for this page, for reference purposes)

University of Kent Author Information

  • Depositors only (login required):

Total unique views for this document in KAR since July 2020. For more details click on the image.