Affiliation:
1. Department of Bioengineering, University of California, Berkeley, CA 94720, USA
Abstract
Abstract
Motivation
Many software libraries for using Hidden Markov Models in bioinformatics focus on inference tasks, such as likelihood calculation, parameter-fitting and alignment. However, construction of the state machines can be a laborious task, automation of which would be time-saving and less error-prone.
Results
We present Machine Boss, a software tool implementing not just inference and parameter-fitting algorithms, but also a set of operations for manipulating and combining automata. The aim is to make prototyping of bioinformatics HMMs as quick and easy as the construction of regular expressions, with one-line ‘recipes’ for many common applications. We report data from several illustrative examples involving protein-to-DNA alignment, DNA data storage and nanopore sequence analysis.
Availability and implementation
Machine Boss is released under the BSD-3 open source license and is available from http://machineboss.org/.
Supplementary information
Supplementary data are available at Bioinformatics online.
Funder
National Institutes of Health
Oxford Nanopore Technologies
Publisher
Oxford University Press (OUP)
Subject
Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Statistics and Probability
Cited by
2 articles.
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