HAMMER algorithm: Hashing with arithmetic modulo-4 for motif extraction of regulatory elements

Huitao Sheng, Kishan Mehrotra, Chilukuri Mohan, Ramesh Raina

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

3 Scopus citations

Abstract

A new algorithm, HAMMER, discovers cis-elements in promoter regions of the co-regulated genes. We show that HAMMER is faster and more accurate than well-known tools currently in use to identify cis-elements. Given input sequences that represent promoter regions of genes, this algorithm searches for subsequences of desired length w whose frequency of occurrence is relatively high, while accounting for slightly corrupted variants (with up to d substitutions). Various w-mers are numerically encoded and represented in a hash table, and d-neighbors are efficiently discovered using a modulo-4 arithmetic operation. Profile matrices are constructed and evaluated using a high-order Markov model based on background data (from a gene database). HAMMER discovers the most frequently occurring w-mers (permitting corruption in at most d positions). Experiment results show that HAMMER is significantly faster and discovers more motifs present in the test sequences, when compared with two well-known motif-discovery tools (MDScan and AlignACE).

Original languageEnglish (US)
Title of host publicationProceedings of the 7th IEEE International Conference on Bioinformatics and Bioengineering, BIBE
Pages753-758
Number of pages6
DOIs
StatePublished - Dec 1 2007
Event7th IEEE International Conference on Bioinformatics and Bioengineering, BIBE - Boston, MA, United States
Duration: Jan 14 2007Jan 17 2007

Publication series

NameProceedings of the 7th IEEE International Conference on Bioinformatics and Bioengineering, BIBE

Other

Other7th IEEE International Conference on Bioinformatics and Bioengineering, BIBE
Country/TerritoryUnited States
CityBoston, MA
Period1/14/071/17/07

ASJC Scopus subject areas

  • Biotechnology
  • Genetics
  • Bioengineering

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