Cargando…

Machine Boss: rapid prototyping of bioinformatic automata

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Silvestre-Ryan, Jordi, Wang, Yujie, Sharma, Mehak, Lin, Stephen, Shen, Yolanda, Dider, Shihab, Holmes, Ian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8034524/
https://www.ncbi.nlm.nih.gov/pubmed/32683444
http://dx.doi.org/10.1093/bioinformatics/btaa633
_version_ 1783676557454213120
author Silvestre-Ryan, Jordi
Wang, Yujie
Sharma, Mehak
Lin, Stephen
Shen, Yolanda
Dider, Shihab
Holmes, Ian
author_facet Silvestre-Ryan, Jordi
Wang, Yujie
Sharma, Mehak
Lin, Stephen
Shen, Yolanda
Dider, Shihab
Holmes, Ian
author_sort Silvestre-Ryan, Jordi
collection PubMed
description 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.
format Online
Article
Text
id pubmed-8034524
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher Oxford University Press
record_format MEDLINE/PubMed
spelling pubmed-80345242021-04-14 Machine Boss: rapid prototyping of bioinformatic automata Silvestre-Ryan, Jordi Wang, Yujie Sharma, Mehak Lin, Stephen Shen, Yolanda Dider, Shihab Holmes, Ian Bioinformatics Original Papers 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. Oxford University Press 2020-07-19 /pmc/articles/PMC8034524/ /pubmed/32683444 http://dx.doi.org/10.1093/bioinformatics/btaa633 Text en © The Author(s) 2020. Published by Oxford University Press. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Papers
Silvestre-Ryan, Jordi
Wang, Yujie
Sharma, Mehak
Lin, Stephen
Shen, Yolanda
Dider, Shihab
Holmes, Ian
Machine Boss: rapid prototyping of bioinformatic automata
title Machine Boss: rapid prototyping of bioinformatic automata
title_full Machine Boss: rapid prototyping of bioinformatic automata
title_fullStr Machine Boss: rapid prototyping of bioinformatic automata
title_full_unstemmed Machine Boss: rapid prototyping of bioinformatic automata
title_short Machine Boss: rapid prototyping of bioinformatic automata
title_sort machine boss: rapid prototyping of bioinformatic automata
topic Original Papers
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8034524/
https://www.ncbi.nlm.nih.gov/pubmed/32683444
http://dx.doi.org/10.1093/bioinformatics/btaa633
work_keys_str_mv AT silvestreryanjordi machinebossrapidprototypingofbioinformaticautomata
AT wangyujie machinebossrapidprototypingofbioinformaticautomata
AT sharmamehak machinebossrapidprototypingofbioinformaticautomata
AT linstephen machinebossrapidprototypingofbioinformaticautomata
AT shenyolanda machinebossrapidprototypingofbioinformaticautomata
AT didershihab machinebossrapidprototypingofbioinformaticautomata
AT holmesian machinebossrapidprototypingofbioinformaticautomata