Finding repetitions in DNA sequences based on a new index-succeeding unit array

Di Wang; Baichen Chen; Qingquan Wu; Yi Zhao; Changyong Yu; Guoren Wang

Finding repetitions in DNA sequences based on a new index-succeeding unit array

Di Wang^*, Baichen Chen, Qingquan Wu, Yi Zhao, Changyong Yu, Guoren Wang

^*Corresponding author for this work

Northeastern University China

Research output: Contribution to journal › Article › peer-review

Abstract

Since the repetitions in a DNA sequence are of great biological significance searching for the repetitions has naturally been an important topic in gene analysis. This paper proposes two new concepts of repetitions-LPR for perfect repetitions and TSAR for approximate repetitions. A lightweight index structure, namely, the Succeeding Unit Array (SUA) is designed based on pattern unit. The SUA decreases the space consumption efficiently and solves the space bottleneck in search of repetitions. On the SUA all the LPRs and TSARs can be detected. The theoretical analysis and experimental results show that both space and time complexity of the algorithms is satisfying.

Original language	English
Pages (from-to)	1371-1378
Number of pages	8
Journal	Journal of Computational Information Systems
Volume	2
Issue number	4
Publication status	Published - Nov 2006
Externally published	Yes

Keywords

LPRs
Repetitions
Succeeding unit array
TSARs

Cite this

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title = "Finding repetitions in DNA sequences based on a new index-succeeding unit array",

abstract = "Since the repetitions in a DNA sequence are of great biological significance searching for the repetitions has naturally been an important topic in gene analysis. This paper proposes two new concepts of repetitions-LPR for perfect repetitions and TSAR for approximate repetitions. A lightweight index structure, namely, the Succeeding Unit Array (SUA) is designed based on pattern unit. The SUA decreases the space consumption efficiently and solves the space bottleneck in search of repetitions. On the SUA all the LPRs and TSARs can be detected. The theoretical analysis and experimental results show that both space and time complexity of the algorithms is satisfying.",

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AU - Wang, Di

AU - Chen, Baichen

AU - Wu, Qingquan

AU - Zhao, Yi

AU - Yu, Changyong

AU - Wang, Guoren

PY - 2006/11

Y1 - 2006/11

N2 - Since the repetitions in a DNA sequence are of great biological significance searching for the repetitions has naturally been an important topic in gene analysis. This paper proposes two new concepts of repetitions-LPR for perfect repetitions and TSAR for approximate repetitions. A lightweight index structure, namely, the Succeeding Unit Array (SUA) is designed based on pattern unit. The SUA decreases the space consumption efficiently and solves the space bottleneck in search of repetitions. On the SUA all the LPRs and TSARs can be detected. The theoretical analysis and experimental results show that both space and time complexity of the algorithms is satisfying.

AB - Since the repetitions in a DNA sequence are of great biological significance searching for the repetitions has naturally been an important topic in gene analysis. This paper proposes two new concepts of repetitions-LPR for perfect repetitions and TSAR for approximate repetitions. A lightweight index structure, namely, the Succeeding Unit Array (SUA) is designed based on pattern unit. The SUA decreases the space consumption efficiently and solves the space bottleneck in search of repetitions. On the SUA all the LPRs and TSARs can be detected. The theoretical analysis and experimental results show that both space and time complexity of the algorithms is satisfying.

KW - LPRs

KW - Repetitions

KW - Succeeding unit array

KW - TSARs

UR - https://www.scopus.com/pages/publications/33845737857

M3 - Article

AN - SCOPUS:33845737857

SN - 1553-9105

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SP - 1371

EP - 1378

JO - Journal of Computational Information Systems

JF - Journal of Computational Information Systems

IS - 4

ER -

Finding repetitions in DNA sequences based on a new index-succeeding unit array

Abstract

Keywords

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