PSAR: Measuring Multiple Sequence Alignment Reliability by Probabilistic Sampling: (Extended Abstract)

Jaebum Kim; Jian Ma

doi:10.1007/978-3-642-20036-6_14

PSAR: Measuring Multiple Sequence Alignment Reliability by Probabilistic Sampling: (Extended Abstract)

Jaebum Kim, Jian Ma

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Multiple sequence alignment (MSA), which is of fundamental importance for comparative genomics, is a difficult problem and error-prone. Therefore, it is essential to measure the reliability of the alignments and incorporate it into downstream analyses. Many studies have been conducted to find the extent, cause and effect of the alignment errors [4], and to heuristically estimate the quality of alignments without using the true alignment, which is unknown [2]. However, it is still unclear whether the heuristically chosen measures are general enough to take into account all alignment errors. In this paper, we present a new alignment reliability score, called PSAR (Probabilistic Sampling-based Alignment Reliability) score.

Original language	English (US)
Title of host publication	Research in Computational Molecular Biology - 15th Annual International Conference, RECOMB 2011, Proceedings
Editors	Vineet Bafna, S. Cenk Sahinalp
Publisher	Springer
Pages	134-135
Number of pages	2
ISBN (Print)	9783642200359
DOIs	https://doi.org/10.1007/978-3-642-20036-6_14
State	Published - 2011
Externally published	Yes
Event	15th Annual International Conference on Research in Computational Molecular Biology, RECOMB 2011 - Vancouver, BC, Canada Duration: Mar 28 2011 → Mar 31 2011

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	6577 LNBI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Other

Other	15th Annual International Conference on Research in Computational Molecular Biology, RECOMB 2011
Country/Territory	Canada
City	Vancouver, BC
Period	3/28/11 → 3/31/11

ASJC Scopus subject areas

Theoretical Computer Science
Computer Science(all)

Online availability

10.1007/978-3-642-20036-6_14

Library availability

Discover UIUC Full Text

Cite this

Kim, J., & Ma, J. (2011). PSAR: Measuring Multiple Sequence Alignment Reliability by Probabilistic Sampling: (Extended Abstract). In V. Bafna, & S. C. Sahinalp (Eds.), Research in Computational Molecular Biology - 15th Annual International Conference, RECOMB 2011, Proceedings (pp. 134-135). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6577 LNBI). Springer. https://doi.org/10.1007/978-3-642-20036-6_14

PSAR: Measuring Multiple Sequence Alignment Reliability by Probabilistic Sampling: (Extended Abstract). / Kim, Jaebum; Ma, Jian.
Research in Computational Molecular Biology - 15th Annual International Conference, RECOMB 2011, Proceedings. ed. / Vineet Bafna; S. Cenk Sahinalp. Springer, 2011. p. 134-135 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6577 LNBI).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Kim, J & Ma, J 2011, PSAR: Measuring Multiple Sequence Alignment Reliability by Probabilistic Sampling: (Extended Abstract). in V Bafna & SC Sahinalp (eds), Research in Computational Molecular Biology - 15th Annual International Conference, RECOMB 2011, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 6577 LNBI, Springer, pp. 134-135, 15th Annual International Conference on Research in Computational Molecular Biology, RECOMB 2011, Vancouver, BC, Canada, 3/28/11. https://doi.org/10.1007/978-3-642-20036-6_14

Kim J, Ma J. PSAR: Measuring Multiple Sequence Alignment Reliability by Probabilistic Sampling: (Extended Abstract). In Bafna V, Sahinalp SC, editors, Research in Computational Molecular Biology - 15th Annual International Conference, RECOMB 2011, Proceedings. Springer. 2011. p. 134-135. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-642-20036-6_14

Kim, Jaebum ; Ma, Jian. / PSAR : Measuring Multiple Sequence Alignment Reliability by Probabilistic Sampling: (Extended Abstract). Research in Computational Molecular Biology - 15th Annual International Conference, RECOMB 2011, Proceedings. editor / Vineet Bafna ; S. Cenk Sahinalp. Springer, 2011. pp. 134-135 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{8d9c2be2076b4944847977938525b2a1,

title = "PSAR: Measuring Multiple Sequence Alignment Reliability by Probabilistic Sampling: (Extended Abstract)",

abstract = "Multiple sequence alignment (MSA), which is of fundamental importance for comparative genomics, is a difficult problem and error-prone. Therefore, it is essential to measure the reliability of the alignments and incorporate it into downstream analyses. Many studies have been conducted to find the extent, cause and effect of the alignment errors [4], and to heuristically estimate the quality of alignments without using the true alignment, which is unknown [2]. However, it is still unclear whether the heuristically chosen measures are general enough to take into account all alignment errors. In this paper, we present a new alignment reliability score, called PSAR (Probabilistic Sampling-based Alignment Reliability) score.",

author = "Jaebum Kim and Jian Ma",

note = "Publisher Copyright: {\textcopyright} 2011, Springer-Verlag Berlin Heidelberg.; 15th Annual International Conference on Research in Computational Molecular Biology, RECOMB 2011 ; Conference date: 28-03-2011 Through 31-03-2011",

year = "2011",

doi = "10.1007/978-3-642-20036-6_14",

language = "English (US)",

isbn = "9783642200359",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer",

pages = "134--135",

editor = "Vineet Bafna and Sahinalp, {S. Cenk}",

booktitle = "Research in Computational Molecular Biology - 15th Annual International Conference, RECOMB 2011, Proceedings",

address = "Germany",

}

TY - GEN

T1 - PSAR

T2 - 15th Annual International Conference on Research in Computational Molecular Biology, RECOMB 2011

AU - Kim, Jaebum

AU - Ma, Jian

PY - 2011

Y1 - 2011

N2 - Multiple sequence alignment (MSA), which is of fundamental importance for comparative genomics, is a difficult problem and error-prone. Therefore, it is essential to measure the reliability of the alignments and incorporate it into downstream analyses. Many studies have been conducted to find the extent, cause and effect of the alignment errors [4], and to heuristically estimate the quality of alignments without using the true alignment, which is unknown [2]. However, it is still unclear whether the heuristically chosen measures are general enough to take into account all alignment errors. In this paper, we present a new alignment reliability score, called PSAR (Probabilistic Sampling-based Alignment Reliability) score.

AB - Multiple sequence alignment (MSA), which is of fundamental importance for comparative genomics, is a difficult problem and error-prone. Therefore, it is essential to measure the reliability of the alignments and incorporate it into downstream analyses. Many studies have been conducted to find the extent, cause and effect of the alignment errors [4], and to heuristically estimate the quality of alignments without using the true alignment, which is unknown [2]. However, it is still unclear whether the heuristically chosen measures are general enough to take into account all alignment errors. In this paper, we present a new alignment reliability score, called PSAR (Probabilistic Sampling-based Alignment Reliability) score.

UR - http://www.scopus.com/inward/record.url?scp=79953177845&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=79953177845&partnerID=8YFLogxK

U2 - 10.1007/978-3-642-20036-6_14

DO - 10.1007/978-3-642-20036-6_14

M3 - Conference contribution

AN - SCOPUS:79953177845

SN - 9783642200359

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 134

EP - 135

BT - Research in Computational Molecular Biology - 15th Annual International Conference, RECOMB 2011, Proceedings

A2 - Bafna, Vineet

A2 - Sahinalp, S. Cenk

PB - Springer

Y2 - 28 March 2011 through 31 March 2011

ER -

PSAR: Measuring Multiple Sequence Alignment Reliability by Probabilistic Sampling: (Extended Abstract)

Abstract

Publication series

Other

ASJC Scopus subject areas

Online availability

Library availability

Related links

Fingerprint

Cite this