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Nucleic Acid Multiple Sequence Analysis

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These are a collection of nucleic acid multiple sequence analysis sites.

[info] THE MEME SYSTEM - Multiple EM for Motif Elicitation
[info] Meta-MEME motif-based hidden Markov models
[info] SCAN-2 Comparison of genomic sequences
[info] VISTA (VISualization Tool for Alignments)

Detailed information on the above options

THE MEME SYSTEM - Multiple EM for Motif Elicitation
MEME is a tool for discovering motifs in a group of related DNA or protein sequences.

A motif is a sequence pattern that occurs repeatedly in a group of related protein or DNA sequences. MEME represents motifs as position-dependent letter-probability matrices which describe the probability of each possible letter at each position in the pattern. Individual MEME motifs do not contain gaps. Patterns with variable-length gaps are split by MEME into two or more separate motifs.

MEME takes as input a group of DNA or protein sequences (the training set) and outputs as many motifs as requested. MEME uses statistical modeling techniques to automatically choose the best width and description for each motif.

Meta-MEME motif-based hidden Markov models
Meta-MEME is a software toolkit for building and using motif-based hidden Markov models of DNA and proteins. The input to Meta-MEME is a set of similar protein sequences, as well as a set of motif models discovered by MEME. Meta-MEME combines these models into a single, motif-based hidden Markov model and uses this model to produce a multiple alignment of the original set of sequences and to search a sequence database for homologs.

SCAN-2 Comparison of genomic sequences
SCAN-2 is developed to compare 2 orthologous regions of some genomes (as Human and Mouse, for example) with Java viewer which helps to investigate and visualize similar subregions. Scan-2 uses a new fast sequence comparison algorithm developed in Softberry Inc.

VISTA (VISualization Tool for Alignments)
VISTA is an integrated system for global alignment and visualization, designed for comparative genomic analysis.

VISTA was developed to locate actively conserved regions between species that contain significant genomic synteny. (Dubchak et al., 2000). With the required input, two orthologous, contiguous sequences from any two species, and the optional input, the annotation of the one you are calling your base sequence, VISTA will align the two sequences and plot the alignment. (We can handle any length up to about a megabase right now.) The regions of high identity, above a cutoff you select, will be colored. If you also include the annotations for this region, the conserved exons will be colored blue, UTRs green, while the non-coding, conserved regions will be in red.

Any Comments, Questions? Support@hgmp.mrc.ac.uk