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A simulation-based approach to statistical alignment

Abstract:

Classic alignment algorithms utilize scoring functions which maximize similarity or minimize edit distances. These scoring functions account for both insertion–deletion (indel) and substitution events. In contrast, alignments based on stochastic models aim to explicitly describe the evolutionary dynamics of sequences by inferring relevant probabilistic parameters from input sequences. Despite advances in stochastic modeling during the last two decades, scoring-based methods are still dominant...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1093/sysbio/syy059

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Institution:
University of Oxford
Division:
MPLS Division
Department:
Statistics
Oxford college:
University College
Role:
Author
Publisher:
Oxford University Press Publisher's website
Journal:
Systematic Biology Journal website
Publication date:
2018-09-15
Acceptance date:
2018-09-10
DOI:
EISSN:
1076-836X
ISSN:
1063-5157
Pubs id:
pubs:923915
URN:
uri:9f7a4e81-19ea-48c4-b982-c46ff456d778
UUID:
uuid:9f7a4e81-19ea-48c4-b982-c46ff456d778
Local pid:
pubs:923915

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