Evaluating bacterial gene-finding HMM structures as probabilistic logic programs
Open Access
- 3 January 2012
- journal article
- research article
- Published by Oxford University Press (OUP) in Bioinformatics
- Vol. 28 (5), 636-642
- https://doi.org/10.1093/bioinformatics/btr698
Abstract
Motivation: Probabilistic logic programming offers a powerful way to describe and evaluate structured statistical models. To investigate the practicality of probabilistic logic programming for structure learning in bioinformatics, we undertook a simplified bacterial gene-finding benchmark in PRISM, a probabilistic dialect of Prolog. Results: We evaluate Hidden Markov Model structures for bacterial protein-coding gene potential, including a simple null model structure, three structures based on existing bacterial gene finders and two novel model structures. We test standard versions as well as ADPH length modeling and three-state versions of the five model structures. The models are all represented as probabilistic logic programs and evaluated using the PRISM machine learning system in terms of statistical information criteria and gene-finding prediction accuracy, in two bacterial genomes. Neither of our implementations of the two currently most used model structures are best performing in terms of statistical information criteria or prediction performances, suggesting that better-fitting models might be achievable. Availability: The source code of all PRISM models, data and additional scripts are freely available for download at: http://github.com/somork/codonhmm. Contact: soer@ruc.dk Supplementary information: Supplementary data are available at Bioinformatics online.This publication has 39 references indexed in Scilit:
- Variational Bayes via propositionalized probability computation in PRISMAnnals of Mathematics and Artificial Intelligence, 2008
- EcoCyc: A comprehensive view of Escherichia coli biologyNucleic Acids Research, 2008
- Deterministic annealing variant of variational Bayes methodJournal of Physics: Conference Series, 2008
- Genie—Gene Finding in Drosophila melanogasterGenome Research, 2000
- Improved microbial gene identification with GLIMMERNucleic Acids Research, 1999
- The Complete Genome Sequence of Escherichia coli K-12Science, 1997
- Prediction of complete gene structures in human genomic DNAJournal of Molecular Biology, 1997
- Finding Genes in DNA with a Hidden Markov ModelJournal of Computational Biology, 1997
- Hidden Markov Models in Computational Biology: Applications to Protein ModelingJournal of Molecular Biology, 1994
- A tutorial on hidden Markov models and selected applications in speech recognitionProceedings of the IEEE, 1989