The statistical significance of nucleotide position-weight matrix matches
نویسندگان
چکیده
منابع مشابه
The statistical significance of nucleotide position-weight matrix matches
MOTIVATION To improve the detection of nucleotide sequence signals (e.g. promoter elements) by position-weight matrices (PWM) using the concept of statistically significant matches. RESULTS The Mksite program was originally developed for analyzing protein sequences. We report NMksite, a new version adapted to the processing of nucleotide sequences. NMksite creates PWM from nucleotide sequence...
متن کاملMOODS: fast search for position weight matrix matches in DNA sequences
UNLABELLED MOODS (MOtif Occurrence Detection Suite) is a software package for matching position weight matrices against DNA sequences. MOODS implements state-of-the-art online matching algorithms, achieving considerably faster scanning speed than with a simple brute-force search. MOODS is written in C++, with bindings for the popular BioPerl and Biopython toolkits. It can easily be adapted for ...
متن کاملOn counting position weight matrix matches in a sequence, with application to discriminative motif finding
MOTIVATION AND RESULTS The position weight matrix (PWM) is a popular method to model transcription factor binding sites. A fundamental problem in cis-regulatory analysis is to "count" the occurrences of a PWM in a DNA sequence. We propose a novel probabilistic score to solve this problem of counting PWM occurrences. The proposed score has two important properties: (1) It gives appropriate weigh...
متن کاملStatistical significance of clusters of motifs represented by position specific scoring matrices in nucleotide sequences.
The human genome encodes the transcriptional control of its genes in clusters of cis-elements that constitute enhancers, silencers and promoter signals. The sequence motifs of individual cis- elements are usually too short and degenerate for confident detection. In most cases, the requirements for organization of cis-elements within these clusters are poorly understood. Therefore, we have devel...
متن کاملPosition Weight Matrix, Gibbs Sampler, and the Associated Significance Tests in Motif Characterization and Prediction
Position weight matrix (PWM) is not only one of the most widely used bioinformatic methods, but also a key component in more advanced computational algorithms (e.g., Gibbs sampler) for characterizing and discovering motifs in nucleotide or amino acid sequences. However, few generally applicable statistical tests are available for evaluating the significance of site patterns, PWM, and PWM scores...
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ژورنال
عنوان ژورنال: Bioinformatics
سال: 1996
ISSN: 1367-4803,1460-2059
DOI: 10.1093/bioinformatics/12.5.431