Propositionalisation of multiple sequence alignments using probabilistic models

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Title

Propositionalisation of multiple sequence alignments using probabilistic models

Content partner

University of Waikato

Collection

ResearchCommons@Waikato

Description

Multiple sequence alignments play a central role in Bioinformatics. Most alignment representations are designed to facilitate knowledge extraction by human experts. Additionally statistical models like Profile Hidden Markov Models are used as representations. They offer the advantage to provide sound, probabilistic scores. The basic idea we present in this paper is to use the structure of a Profile Hidden Markov Model for propositionalisation. This way we get a simple, extendable representati...

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Format

Research paper

Research format

Conference item

Date created

2008

Creator

Mutter, Stefan / Pfahringer, Bernhard / Holmes, Geoffrey

URL

https://hdl.handle.net/10289/8107

Related subjects

computer science / multiple sequence alignment representation / Hidden Markov Model / propositionalisation / Machine learning

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