New scoring schema for finding motifs in DNA Sequences

Abstract

Background: Pattern discovery in DNA sequences is one of the most fundamental problems in molecular biology with important applications in finding regulatory signals and transcription factor binding sites. An important task in this problem is to search (or predict) known binding sites in a new DNA sequence. For this reason, all subsequences of the given DNA sequence are scored based on an scoring function and the prediction is done by selecting the best score. By assuming no dependency between binding site base positions, most of the available tools for known binding site prediction are designed. Recently Tomovic and Oakeley investigated the statistical basis for either a claim of dependence or independence, to determine whether such a claim is generally true, and they presented a scoring function for binding site prediction based on the dependency between binding site base positions. Our primary objective is to investigate the scoring functions which can be used in known binding site prediction based on the assumption of dependency or independency in binding site base positions.

Expression of the forkhead transcription factor FOXL2 correlates with good prognosis in breast cancer patients treated with tamoxifen

“…According to the results, I.7 is a more interesting target than I.3/II as three perfect matches and two nearly perfect matches (only 1 mismatch against the consensus) of the FLRE were found in this promoter as opposed to only two nearly perfect matches in I.3/II. Benayoun et al (17) found that the number of FLREs in the promoter reflects the amplitude of the response, as an artificial luciferase promoter reporter containing four FLrE sequences has significantly higher expression levels than a promoter containing only two FLrEs. moreover, they concluded that the number of identified FLREs is significantly higher in the promoter sequences of FOXL2-responsive genes compared to all the promoter sequences in the remaining genome.…”

“…The first search involved a simple matching approach, where the matching score (score C) is the number of mismatches to the motif when compared to a subsequence of the promoter. The second search was based on the position weight matrix of the cis-elements and the matching score (score n) was calculated using the independent scoring scheme described by Zaremirakabad et al (17), i.e., it was assumed that all positions in a given motif are completely independent. The motif consensus and position weight matrix were derived from the study by Benayoun et al (18).…”

Numerous recursive sites contribute to accuracy of splicing of long introns in flies

“…We assumed that variance in read density at each position was proportional to the coverage level at that position, which is likely true since RNA-seq read coverage is intrinsically the sum of Bernoulli random variables. To calculate these regressions, we developed a function that made use of the Scipy stats weighted linear regression function [20] as a sub-process, such that: Note that − ≤ 10 #S checks whether all weights have changed by at most 10 -3 .…”

Mechanisms and Evolution of Control Logic in Prokaryotic Transcriptional Regulation

“…Importantly, this model also takes into account the binding affinity of a TF for the background sequence. Also, nucleotide interdependencies have started to be modeled into motif discovery algorithms (222,327,330). In complex promoters where homocooperative regulation takes place, there is a good chance that fuzzy motifs that function specifically to bind TFs with weak affinity are not incorporated in in silico predictions because of a lack of statistical significance.…”