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TransFind-potential transcription factor complexes

MEME,tfsearch




TransFind is a tool for the identification of potential transcription factor complexes several genes in a genelist have in common. TransFind can be used for searching transcription factor binding sites results from MEME , GIBBS , & TESS visually. Transfind can also be used to create an oligonucleotide decoy for a transcription factor of interest and move forward in RNAi target selection. Recent uses for this tool have included the prediction of DAG/PKC transcription factors.


Current version: 2.1
MEME results visualization & identification of potential transcription factor complexes...More Info...


BioCanvas-graphics software for proteomics and genomics

BioCanvas-graphics software for proteomics and genomics


BioCanvas is a powerful graphics software for proteomics and genomics. Easily carry out prokaryote and eukaryote desktop comparative genomics with this tool. Powered by a pre-computed BLAST database of over 72 organisms and the ability to import new organism files in FASTA DNA ,FASTA AA and Genbank formats scientists can easily create a robust and customized data storage, annotation and data mining environment. With distributed BLAST, automatic orf finding, alignment features for visual contig assembly & several views this package is a must have for anyone doing comparative genomics research.


Current version: 2.7
More info on this powerful graphics software for proteomics and genomics...




Customer Spotlight
07/16/2006 - Dupont Licenses additional copies of BioCanvas
07/13/2005 - UK Human Genome Mapping Project Licenses Genomic Discovery Tool's TransFind
12/10/2005 - Genomic Discovery Tools Delivers Version 2.1 Of TransFind Transcription Factor Binding Site Locator Software


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sitemap MEME
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, number of occurrences, and description for each motif. MEME sends you three e-mail messages: a confirmation message, the MEME results, and the MAST results of searching the training set for the motifs found by MEME using MAST. Occurrences of the Motif MEME displays the occurrences (sites) of the motif in the training set. The sites are shown aligned with each other, the ten sequence positions preceding &following are shown.

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