Identification of transcription factor binding sites based on the chi-square (χ2) distance of a probabilistic vector model

Lun Huang, Mohammad Al Bataineh, G. E. Atkin, Ismaeel Mohammed, Wei Zhang, Maria Parra, Maria Del Mar Perez

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

4 Citations (Scopus)

Abstract

This paper describes a new approach for locating signals, such as promoter sequences, in nucleic acid sequences. Transcription Factor (TF) binding to its DNA target site is a fundamental regulatory interaction. The most common model used to represent TF binding specificities is a position weight matrix (PWM) [1], which assumes independence between binding positions. However, in many cases, this simplifying assumption does not hold. In this paper, we present a Chi-Square (χ2) distance model [2], which is based on the distance between the profiles of component vectors. It is a novel probabilistic method for modeling TF-DNA interactions. Our approach uses χ2 distances to represent TF binding specificities. Simulation results show that the proposed approach identifies TF binding sites significantly better than the PWM model method.

Original languageEnglish
Title of host publicationFBIE 2009 - 2009 International Conference on Future BioMedical Information Engineering
Pages73-76
Number of pages4
DOIs
Publication statusPublished - 2009
Externally publishedYes
Event2009 International Conference on Future BioMedical Information Engineering, FBIE 2009 - Sanya, China
Duration: Dec 13 2009Dec 14 2009

Publication series

NameFBIE 2009 - 2009 International Conference on Future BioMedical Information Engineering

Conference

Conference2009 International Conference on Future BioMedical Information Engineering, FBIE 2009
Country/TerritoryChina
CitySanya
Period12/13/0912/14/09

Keywords

  • Chi-square distance
  • Promoter
  • Transcription factor

ASJC Scopus subject areas

  • Biomedical Engineering
  • Health Informatics
  • Health Information Management

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