HMMoC--a compiler for hidden Markov models.

Journal article

UNLABELLED: Hidden Markov models are widely applied within computational biology. The large data sets and complex models involved demand optimized implementations, while efficient exploration of model space requires rapid prototyping. These requirements are not met by existing solutions, and hand-coding is time-consuming and error-prone. Here, I present a compiler that takes over the mechanical process of implementing HMM algorithms, by translating high-level XML descriptions into efficient C++ implementations. The compiler is highly customizable, produces efficient and bug-free code, and includes several optimizations. AVAILABILITY: http://genserv.anat.ox.ac.uk/software.

Authors: Lunter, G

• Publication status: Published
• Journal: Bioinformatics (Oxford, England)
• Volume: 23
• Issue: 18
• Pages: 2485-2487
• Publication date: 2007-09-01
• DOI: 10.1093/bioinformatics/btm350
• EISSN: 1367-4811
• ISSN: 1367-4803
• Language: English
• Keywords: Artificial Intelligence; Computational Biology; Programming Languages; Models, Biological; Computer Simulation; Sequence Analysis; Pattern Recognition, Automated; Models, Statistical; Software; Markov Chains; Algorithms