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Bioinformatics methods for the analysis of expression arrays: data clustering and information extraction
Javier Tamames1, Dominic Clark, Javier Herrero
1ALMA Bioinformatics, S.L., Spain.
Journal of Biotechnology
|July 27, 2002
Summary
This study reviews bioinformatics technologies for analyzing gene expression data. It highlights key stages like image analysis and gene clustering, focusing on advancements in these areas.
Area of Science:
- Bioinformatics
- Genomics
- Computational Biology
Background:
- Gene expression arrays enable monitoring of large-scale gene expression changes.
- Analysis of expression array data presents significant computational challenges.
Purpose of the Study:
- To review current trends in bioinformatics technology for expression array data analysis.
- To highlight technological developments in key analysis stages.
Main Methods:
- Review of existing bioinformatics technologies.
- Emphasis on image analysis, database storage, gene clustering, and information extraction.
- Focus on technologies developed within the authors' research groups.
Main Results:
- Identification of computational challenges in expression array data analysis.
- Overview of advancements in bioinformatics tools for gene expression studies.
- Specific focus on image analysis, data storage, clustering, and information extraction.
Conclusions:
- Bioinformatics technology is crucial for efficient expression array data analysis.
- Ongoing development in key areas is essential for advancing genomic research.
- The reviewed technologies offer improved capabilities for gene expression monitoring.