Finding Possible Promoter Binding Sites in DNA Sequences by Sequential Patterns Mining with Specific Numbers of Gaps

Yu Hao Ke, Jen Wei Huang, Wei Chen Lin, Bijay Prasad Jaysawal

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)

Abstract

Identifying motifs in promoter regions is crucial to our understanding of transcription regulation. Researchers commonly use known promoter features in a variety of species to predict promoter motifs. However the results are not particularly useful. Different species rarely have similar features in promoter binding sites. In this study, we adopt sequence analysis techniques to find the possible promoter binding sites among different species. We sought to improve the existing algorithm to suit the task of mining sequential patterns with specific number of gaps. Moreover, we discuss the implementation of proposed method in a distributed environment. The proposed method finds the transcription start sites (TSS) and extracts possible promoter regions from DNA sequences according to TSS. We derived the motifs in the possible promoter regions, while taking into account the number of gaps in the motifs to deal with unimportant nucleotides. The motifs generated from promoter regions using the proposed methodology were shown to tolerate unimportant nucleotides. A comparison with known promoter motifs verified the efficacy of the proposed method.

Original languageEnglish
Pages (from-to)2459-2470
Number of pages12
JournalIEEE/ACM Transactions on Computational Biology and Bioinformatics
Volume18
Issue number6
DOIs
Publication statusPublished - 2021

All Science Journal Classification (ASJC) codes

  • Biotechnology
  • Genetics
  • Applied Mathematics

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