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Identification of transcription factor binding sites based on the Chi-Square (x2) distance of a probabilistic vector model

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7 Author(s)
Lun Huang ; ECE, Illinois Institute of Technology, Chicago, U.S.A. ; Mohammad Al Bataineh ; G. E. Atkin ; Ismaeel Mohammed
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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), which assumes independence between binding positions. However, in many cases, this simplifying assumption does not hold. In this paper, we present a Chi-square ( x2 ) distance model, 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 x2 distances to represent TF binding specificities. Simulation results show that the proposed approach identifies TF binding sites significantly better than the PWM model method.

Published in:

2009 International Conference on Future BioMedical Information Engineering (FBIE)

Date of Conference:

13-14 Dec. 2009