A practical approach to significance assessment in alignment with gaps

Nicholas Chia; Ralf Bundschuh

doi:10.1007/11415770_36

A practical approach to significance assessment in alignment with gaps

Nicholas Chia, Ralf Bundschuh

Research output: Contribution to journal › Conference article › peer-review

2 Scopus citations

Abstract

Current numerical methods for assessing the statistical significance of local alignments with gaps are time consuming. Analytical solutions thus far have been limited to specific cases. Here, we present a new line of attack to the problem of statistical significance assessment. We combine this new approach with known properties of the dynamics of the global alignment algorithm and high performance numerical techniques and present a novel method for assessing significance of gaps within practical time scales. The results and performance of these new methods test very well against tried methods with drastically less effort.

Original language	English (US)
Pages (from-to)	474-488
Number of pages	15
Journal	Lecture Notes in Bioinformatics (Subseries of Lecture Notes in Computer Science)
Volume	3500
DOIs	https://doi.org/10.1007/11415770_36
State	Published - 2005
Event	9th Annual International Conference on Research in Computational Molecular Biology, RECOMB 2005 - Cambridge, MA, United States Duration: May 14 2005 → May 18 2005

Keywords

Asymmetric exclusion process
Extreme value distribution
Gumbel distribution
Kardar-Parisi-Zhang universality class
Markov models and/or hidden Markov models
Pairwise sequence alignment
Statistical significance
Statistics of motifs or strings

ASJC Scopus subject areas

Theoretical Computer Science
Computer Science(all)

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10.1007/11415770_36

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@article{2a2219cd5fcd4c4abbb5d8b3a4715505,

title = "A practical approach to significance assessment in alignment with gaps",

abstract = "Current numerical methods for assessing the statistical significance of local alignments with gaps are time consuming. Analytical solutions thus far have been limited to specific cases. Here, we present a new line of attack to the problem of statistical significance assessment. We combine this new approach with known properties of the dynamics of the global alignment algorithm and high performance numerical techniques and present a novel method for assessing significance of gaps within practical time scales. The results and performance of these new methods test very well against tried methods with drastically less effort.",

keywords = "Asymmetric exclusion process, Extreme value distribution, Gumbel distribution, Kardar-Parisi-Zhang universality class, Markov models and/or hidden Markov models, Pairwise sequence alignment, Statistical significance, Statistics of motifs or strings",

author = "Nicholas Chia and Ralf Bundschuh",

year = "2005",

doi = "10.1007/11415770_36",

language = "English (US)",

volume = "3500",

pages = "474--488",

journal = "Lecture Notes in Bioinformatics (Subseries of Lecture Notes in Computer Science)",

issn = "0302-9743",

publisher = "Springer Verlag",

note = "9th Annual International Conference on Research in Computational Molecular Biology, RECOMB 2005 ; Conference date: 14-05-2005 Through 18-05-2005",

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TY - JOUR

T1 - A practical approach to significance assessment in alignment with gaps

AU - Chia, Nicholas

AU - Bundschuh, Ralf

PY - 2005

Y1 - 2005

N2 - Current numerical methods for assessing the statistical significance of local alignments with gaps are time consuming. Analytical solutions thus far have been limited to specific cases. Here, we present a new line of attack to the problem of statistical significance assessment. We combine this new approach with known properties of the dynamics of the global alignment algorithm and high performance numerical techniques and present a novel method for assessing significance of gaps within practical time scales. The results and performance of these new methods test very well against tried methods with drastically less effort.

AB - Current numerical methods for assessing the statistical significance of local alignments with gaps are time consuming. Analytical solutions thus far have been limited to specific cases. Here, we present a new line of attack to the problem of statistical significance assessment. We combine this new approach with known properties of the dynamics of the global alignment algorithm and high performance numerical techniques and present a novel method for assessing significance of gaps within practical time scales. The results and performance of these new methods test very well against tried methods with drastically less effort.

KW - Asymmetric exclusion process

KW - Extreme value distribution

KW - Gumbel distribution

KW - Kardar-Parisi-Zhang universality class

KW - Markov models and/or hidden Markov models

KW - Pairwise sequence alignment

KW - Statistical significance

KW - Statistics of motifs or strings

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U2 - 10.1007/11415770_36

DO - 10.1007/11415770_36

M3 - Conference article

AN - SCOPUS:26444490663

SN - 0302-9743

VL - 3500

SP - 474

EP - 488

JO - Lecture Notes in Bioinformatics (Subseries of Lecture Notes in Computer Science)

JF - Lecture Notes in Bioinformatics (Subseries of Lecture Notes in Computer Science)

T2 - 9th Annual International Conference on Research in Computational Molecular Biology, RECOMB 2005

Y2 - 14 May 2005 through 18 May 2005

ER -

A practical approach to significance assessment in alignment with gaps

Abstract

Keywords

ASJC Scopus subject areas

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