Positional Weight Matrix as a Sequence Motif Detector

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TypeBook Chapter
Book titleOligonucleotide Array Sequence Analysis
ISBN978-1-60456-542-3
Pages421440; # of pages: 20
AbstractIn biological sequence research, the positional weight matrix (PWM) is often used for motif signal detection. A set of experimentally verified oligonucleotides known to be functional subsequences, which can be bound by a transcription factor (TF), as translational initiation sites or pre-mRNA splicing sites, are collected and aligned. The frequency of each nucleotide A, C, G, or T at each column of the alignment is calculated in the matrix. Once a PWM is constructed, it can be used to search from a nucleotide sequence for the subsequences that possibly perform the same function. The match between a subsequence and a PWM is usually described by a score function, which measures the closeness of the subsequence to the PWM as compared with the given background. However, selection of threshold scores that legitimately qualify a functional subsequence has been a great challenge. Many laboratories have attempted tackling this problem; but there is no significant breakthrough so far. In this chapter, we discuss the characteristics of a PWM and factors that affect motif predictions and propose a new score function that is tied into information content and statistical expectation of a PWM. We also apply this score function in the PWMs from public databases and compare it favorably with the broadly used Match method.
Publication date
PublisherNova Science Publishers
LanguageEnglish
AffiliationNRC Institute for Information Technology; National Research Council Canada
Peer reviewedNo
NRC number50391
NPARC number5764985
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Record identifierea9161ea-ede6-4c8c-8794-afca7eac4710
Record created2009-03-29
Record modified2016-05-09
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