Constrained Hidden Markov Models in PRISM

This is the webpage is the home of an implementation of Constrained Hidden Markov Models in PRISM. The particular implementation use a pair HMM example which is usuable for constrained sequence alignment. The implementation includes a few well-known global constraints which may be used with the model. The purpose of this implementation is to illustrate a method for adding side-constraints to HMMs expressed in PRISM. The implementation is described in detail in our ICLP 2010 paper:

Henning Christiansen, Christian Theil Have, Ole Torp Lassen and Matthieu Petit
"Inference with Constrained Hidden Markov Models in PRISM".
Abstract: A Hidden Markov Model (HMM) is a common statistical model which is widely used for analysis of biological sequence data and other sequential phenomena. In the present paper we show how HMMs can be extended with side-constraints and present constraint solving techniques for efficient inference. Defining HMMs with side-constraints in Constraint Logic Programming have advantages in terms of more compact expression and pruning opportunities during inference. We present a PRISM-based framework for extending HMMs with side-constraints and show how well-known constraints such as cardinality and all_different are integrated. We experimentally validate our approach on the biologically motivated problem of global pairwise alignment.


Downloads

Instructions on how to use the code is contained the README files which are downloaded with the code.

Usage

This software can be downloaded and used for free for any peaceful and non-commercial purpose. The developer take no responsibility for any consequences of the use of this software. For possible commercial applications, or if any doubts concerning these conditions, please write to the developer.

This software was developed as part of the lost project.
Last modified Wed Apr 7 10:03:32 CEST 2010