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Investigating Protein Sequence-structure-dynamics Relationships with Bio3D-web
Published on: July 16, 2017
MEME: discovering and analyzing DNA and protein sequence motifs
Timothy L Bailey1, Nadya Williams, Chris Misleh
1Institute of Molecular Bioscience, The University of Queensland, St Lucia, QLD 4072, Australia. t.bailey@imb.uq.edu.au
Nucleic Acids Research
|July 18, 2006
Summary
Multiple EM for Motif Elicitation (MEME) identifies novel sequence patterns in biological data. This widely used tool aids in discovering transcription factor binding sites and protein domains via a web server.
Area of Science:
- Bioinformatics
- Computational Biology
- Genomics
Background:
- Identifying functional elements in biological sequences is crucial for understanding gene regulation and protein function.
- Novel sequence patterns, such as transcription factor binding sites and protein domains, are key biological signals.
- Existing tools require efficient methods for discovering and analyzing these patterns.
Purpose of the Study:
- To describe the MEME (Multiple EM for Motif Elicitation) web server and its capabilities.
- To provide guidance on effectively using MEME for discovering and analyzing sequence patterns.
- To highlight the utility of MEME in identifying novel biological signals.
Main Methods:
- MEME utilizes the Multiple EM for Motif Elicitation algorithm to find ungapped sequence patterns.
- Searches are performed on user-provided DNA or protein sequences.
- The MEME web server offers access to motif discovery, alignment, and searching functionalities.
Main Results:
- MEME successfully identifies repeated, ungapped sequence patterns within biological datasets.
- The web server facilitates comparison of discovered motifs with known motif databases.
- Users can search sequence databases for matches to identified motifs.
Conclusions:
- MEME is a powerful and accessible tool for discovering novel sequence patterns in biological data.
- The web server enhances the usability and application of MEME for researchers.
- Effective use of MEME aids in the analysis and significance assessment of biological sequence patterns.
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