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Using SCOPE to Identify Potential Regulatory Motifs in Coregulated Genes
Published on: May 31, 2011
Minimotif miner 2nd release: a database and web system for motif search
Sanguthevar Rajasekaran1, Sudha Balla, Patrick Gradie
1Department of Computer Science and Engineering, University of Connecticut, Storrs, CT 06029-2155, USA. rajasek@engr.uconn.edu
Nucleic Acids Research
|November 4, 2008
Summary
Minimotif Miner (MnM) is a tool for predicting protein functions using motifs. The revised version 2 features a 10-fold larger database and enhanced analysis capabilities for proteins and SNPs.
Area of Science:
- Bioinformatics
- Computational Biology
- Molecular Biology
Background:
- Minimotif Miner (MnM) is a web-based application for predicting protein functions based on minimotifs.
- The previous version provided a foundational tool for motif-based functional analysis.
Purpose of the Study:
- To present the revised Minimotif Miner (MnM) version 2, highlighting significant database expansion and user interface improvements.
- To enhance the prediction accuracy and user experience for motif-based functional analysis in proteins and SNPs.
Main Methods:
- Expanded the minimotif database to approximately 5000 motifs.
- Standardized motif function definitions for consistency.
- Redeveloped the web application with improved navigation and new features like screencast help and alias name support.
- Integrated expanded Single Nucleotide Polymorphism (SNP) analysis capabilities.
Main Results:
- The MnM database now contains over 5000 motifs, a tenfold increase from the previous version.
- The updated web application offers a more intuitive user interface and enhanced analytical functions.
- Demonstrated the utility of MnM 2 through a sample analysis of prion protein data.
Conclusions:
- Minimotif Miner version 2 offers a substantially improved platform for motif-based protein function prediction.
- The expanded database and enhanced features provide researchers with a more powerful tool for biological data analysis.
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