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Machine Boss: rapid prototyping of bioinformatic automata.


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.

SUBMITTER: Silvestre-Ryan J 

PROVIDER: S-EPMC8034524 | biostudies-literature | 2021 Apr

REPOSITORIES: biostudies-literature

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Publications

Machine Boss: rapid prototyping of bioinformatic automata.

Silvestre-Ryan Jordi J   Wang Yujie Y   Sharma Mehak M   Lin Stephen S   Shen Yolanda Y   Dider Shihab S   Holmes Ian I  

Bioinformatics (Oxford, England) 20210401 1


<h4>Motivation</h4>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.<h4>Results</h4>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 aut  ...[more]

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