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16:41
A Protocol for Computer-Based Protein Structure and Function Prediction
Published on: November 3, 2011
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Eliciting the Functional Taxonomy from protein annotations and taxa
Marco Falda1, Enrico Lavezzo1, Paolo Fontana2
1Department of Molecular Medicine, University of Padova, Padova, 35131, Italy.
Scientific Reports
|August 19, 2016
Summary
FunTaxIS infers functional taxonomy by integrating omics data and Gene Ontology (GO) annotations. This tool maps biological functions across species, revealing distribution patterns and knowledge gaps.
Area of Science:
- Bioinformatics
- Computational Biology
- Genomics
Background:
- Omics technologies generate vast species-specific data.
- Gene Ontology (GO) provides protein functional information.
- Integrating these datasets is crucial for understanding biological functions across taxa.
Purpose of the Study:
- To develop FunTaxIS, the first tool for inferring functional taxonomy.
- To map the distribution of biological functions across different taxa.
- To enable comparative functional analyses and identify knowledge gaps.
Main Methods:
- FunTaxIS defines taxon-specific functional spaces using annotation frequencies.
- It generates constraints between GO terms and taxa.
- These constraints are propagated across the taxonomic tree and GO graph.
Main Results:
- The tool successfully maps functions across the taxonomy.
- It can identify improper taxon-function associations.
- It highlights how functional knowledge is distributed or missing.
Conclusions:
- FunTaxIS provides a novel approach to functional taxonomy inference.
- The tool facilitates comparative functional analyses and data quality assessment.
- It aids in understanding the evolutionary distribution of biological functions.
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