Some biosequence motifs exhibit insertions and deletions, but MEME cannot discover such motifs, because it does not allow gaps.
#Differences imeme how to#
Detailed protocols describing how to use MEME are available ( 8). The MEME algorithm ( 2) has been widely used for the discovery of DNA and protein sequence motifs, and MEME continues to be the starting point for most analyses using the MEME Suite. Opal provides job management services allowing the MEME Suite to queue multiple simultaneous requests. These are published as SOAP (Simple Object Access Protocol) web services using Opal ( 7) and the Tomcat Java servlet container. The components of the MEME Suite are implemented in ANSI C as command line tools. MEME ( 2) and GLAM2 ( 3) are tools for motif discovery, T omtom ( 4) searches for similar motifs in databases of known motifs, FIMO, GLAM2SCAN ( 3) and MAST ( 5) search for occurrences of motifs in sequence databases, and GOMO ( 6) provides associations between motifs and GO terms. Figure 1 shows an overview of the MEME Suite. It offers a significantly expanded set of programs for these tasks compared with the earlier web server ( 1).
#Differences imeme software#
The MEME Suite is a software toolkit with a unified web server interface that enables users to perform four types of motif analysis: motif discovery, motif–motif database searching, motif-sequence database searching and assignment of function. Source code, binaries and a web server are freely available for noncommercial use at. All of the motif-based tools are now implemented as web services via Opal. GLAM2 output similarly contains buttons for further analysis using GLAM2SCAN and for rerunning GLAM2 with different parameters. MEME output now contains sequence LOGOS for each discovered motif, as well as buttons to allow motifs to be conveniently submitted to the sequence and motif database scanning algorithms (MAST, FIMO and T omtom), or to GOMO, for further analysis. Transcription factor motifs can be further analyzed for putative function by association with Gene Ontology (GO) terms using the motif-GO term association tool GOMO. Transcription factor motifs (including those discovered using MEME) can be compared with motifs in many popular motif databases using the motif database scanning algorithm T omtom. Three sequence scanning algorithms-MAST, FIMO and GLAM2SCAN-allow scanning numerous DNA and protein sequence databases for motifs discovered by MEME and GLAM2. The popular MEME motif discovery algorithm is now complemented by the GLAM2 algorithm which allows discovery of motifs containing gaps. The MEME Suite web server provides a unified portal for online discovery and analysis of sequence motifs representing features such as DNA binding sites and protein interaction domains.
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