DNA numerical representation and neural network based human promoter prediction system

Swarna Bai Arniker, Hon Keung Kwan, Ngai Fong Law, Pak Kong Lun

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

6 Citations (Scopus)

Abstract

In spite of the recent development of computational methods for human promoter prediction, the prediction performance still needs improvement. In particular, the high false positive rate of the traditional approaches decreases the prediction reliability and leads to erroneous results in gene annotation. To improve the prediction accuracy and reliability, a DNA numerical representation and neural network based approach is studied for characterizing DNA alphabets in different regions of a DNA sequence. Three mapping functions are used for converting the DNA alphabets to numerical values so that discriminative biological features are extracted for promoter prediction. Simulations of the proposed system were carried out using a set of genomic sequences from the human chromosome 22 and it was found to achieve high sensitivity and specificity.
Original languageEnglish
Title of host publicationProceedings - 2011 Annual IEEE India Conference
Subtitle of host publicationEngineering Sustainable Solutions, INDICON-2011
DOIs
Publication statusPublished - 1 Dec 2011
Event2011 Annual IEEE India Conference: Engineering Sustainable Solutions, INDICON-2011 - Hyderabad, India
Duration: 16 Dec 201118 Dec 2011

Conference

Conference2011 Annual IEEE India Conference: Engineering Sustainable Solutions, INDICON-2011
Country/TerritoryIndia
CityHyderabad
Period16/12/1118/12/11

Keywords

  • bioinformatics
  • DNA numerical representation
  • neural networks
  • promoter recognition

ASJC Scopus subject areas

  • Renewable Energy, Sustainability and the Environment

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