Machine Boss: rapid prototyping of bioinformatic automata

Author:

Silvestre-Ryan Jordi1ORCID,Wang Yujie1,Sharma Mehak1,Lin Stephen1,Shen Yolanda1,Dider Shihab1ORCID,Holmes Ian1

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

Reference51 articles.

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