DiCE: Discovery of conserved noncoding sequences efficiently

Sairam Behera, Xianjun Li, James Schnable, Jitender S. Deogun

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Identification of the conserved non-coding sequences (CNSs) for plants is a challenging problem because the plants have small CNSs compared to animals. The existing alignment based methods are neither efficient nor sensitive to smaller CNSs when the number of species is large. In this paper, we propose an alignment-free approach that can process any number sequences simultaneously. Our approach uses maximal repeats extracted from generalized suffix tree of the sequences and discovers both exactly matched CNSs as well as CNSs with a given mismatch rate. The experimental results with 17, 996 syntenic genes of six grass species shows that our approach is more efficient than existing approaches.

Original languageEnglish (US)
Title of host publicationProceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017
EditorsIllhoi Yoo, Jane Huiru Zheng, Yang Gong, Xiaohua Tony Hu, Chi-Ren Shyu, Yana Bromberg, Jean Gao, Dmitry Korkin
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages79-82
Number of pages4
ISBN (Electronic)9781509030491
DOIs
StatePublished - Dec 15 2017
Externally publishedYes
Event2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017 - Kansas City, United States
Duration: Nov 13 2017Nov 16 2017

Publication series

NameProceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017
Volume2017-January

Other

Other2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017
Country/TerritoryUnited States
CityKansas City
Period11/13/1711/16/17

Keywords

  • CNS
  • DAG
  • MEM
  • Suffix tree

ASJC Scopus subject areas

  • Biomedical Engineering
  • Health Informatics

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