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A discriminative approach to structured biological data

Abstract
This paper introduces the first author’s PhD project which has just got out of its initial stage. Biological sequence data is, on the one hand, highly structured. On the other hand there are large amounts of unlabelled data. Thus we combine probabilistic graphical models and semi-supervised learning. The former to handle structured data and latter to deal with unlabelled data. We apply our models to genotype-phenotype modelling problems. In particular we predict the set of Single Nucleotide Polymorphisms which underlie a specific phenotypical trait.
Type
Conference Contribution
Type of thesis
Series
Citation
Mutter, S. & Pfahringer, B. (2007). A discriminative approach to structured biological data. In Proceedings of NZCSRSC'07, the Fifth New Zealand Computer Science Research Student Conference. The University of Waikato, Hamilton, New Zealand, 10-13 April 2007, 2007(pp.1-4).
Date
2007
Publisher
The University of Waikato
Degree
Supervisors
Rights