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MOST - A web tool for the extraction of motifs in DNA sequences

MOST is a web tool for the extraction of motifs in DNA sequences. Motifs are extracted by completing a series of analysis steps, starting with searching for"most surprising" brief exact patterns, on the basis of a selected score, and continuing with clustering of exact patterns to produce "core motifs", which undergo to following analysis and are enlarged to generate extended motifs. The five analysis steps are described briefly below and in detail in the help page. Orientate with the step indicator: the current step is yellow, completed steps are green and following steps are red.
Step 1 Exact pattern extraction The program Verbumculus extract "most surprising" exact pattern, according to a series of selected parameters.
Step 2 View words table You can browse your results, order them according to score, number of occurrences and number of sequences and select the number of words for the following analysis.
Step 3 Cluster parameters selection Exact patterns are clustered to build "core motifs". A threshold of similarity must be chosen for clustering.
Step 4 View clustering Result Results of the clustering are displayed in a summary table. Details of word composition of each cluster, matrix of nucloetide frequencies in "core morif" positions and consensus sequence are shown. The positions of maximum of 10 different "core motifs" on the input sequences could be visualized by a graphycal tool.
Step 5 Extension Parameter Selection The output of the previous step is the core of the motifs you are looking for. In order to obtain the total motif you have to select the lengths of the borders besides the core.
Step 6 Visualise Results A summary table will display the results of motif extension and selection. The positions of maximum of 10 different extended motifs on the input sequences could be visualized by a graphycal tool.

Cover figure Pizzi C, Bortoluzzi S, Bisognin A, Coppe A, Danieli GA.
Detecting seeded motifs in DNA sequences.
Nucl. Acids. Res. 2005, 33(15).
Open Access
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