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TissueInfo: high-throughput identification of tissue expression profiles and specificity.
1Institute for Computational Biomedicine and Department of Physiology and Biophysics, Mount Sinai School of Medicine, Box 1218, 1 Gustave L. Levy Place, New York, NY 10029, USA.
Nucleic Acids Research
|November 3, 2001
Summary
TissueInfo is a new computational method that accurately identifies gene tissue expression profiles and specificity. This tool aids in gene discovery and selecting genes for research applications like custom microarrays.
Area of Science:
- Bioinformatics
- Computational Biology
- Genomics
Background:
- High-throughput identification of tissue expression profiles and specificity is crucial for understanding gene function.
- Existing methods may lack the scalability or accuracy required for large-scale genomic analysis.
Purpose of the Study:
- To introduce TissueInfo, a knowledge-based method for high-throughput identification of tissue expression profiles and specificity.
- To provide a tool for data mining and selection of genes based on expression patterns.
Main Methods:
- TissueInfo utilizes a set of tissue information calculations applicable to genes, expressed sequence tags (ESTs), and proteins.
- Calculated tissue information records are used to generate data mining tables.
- Benchmarking was performed against 116 proteins and literature data.
Main Results:
- TissueInfo achieved 69% accuracy for tissue specificities and 80% for expression profiles.
- Ignoring sequences with limited dbEST data improved accuracy to 76% for specificity and 89% for expression (at 80% coverage).
- Compared to SWISS-PROT's curated data (78% accuracy), TissueInfo demonstrates competitive performance.
Conclusions:
- TissueInfo is an accurate and efficient tool for identifying tissue expression profiles and specificity.
- The method is valuable for selecting clones for custom microarrays, training sets for ab initio identification, gene discovery, and genome-wide predictions.