Prediction of human protein function according to Gene Ontology categories
| Autor: | Søren Brunak, Hans Henrik Stærfeldt, Lars Juhl Jensen, Ramneek Gupta |
|---|---|
| Rok vydání: | 2003 |
| Předmět: |
Statistics and Probability
Hypothetical protein Information Storage and Retrieval Sequence Homology Biology Biochemistry Pattern Recognition Automated Structure-Activity Relationship Sequence Analysis Protein Humans Protein function prediction Databases Protein Critical Assessment of Function Annotation Molecular Biology Gene Sequence (medicine) Genetics Gene Expression Profiling Proteins Computer Science Applications Computational Mathematics Protein Sorting Signals Computational Theory and Mathematics Database Management Systems Human genome Neural Networks Computer Sequence Alignment Algorithms Function (biology) |
| Zdroj: | University of Copenhagen |
| ISSN: | 1367-4811 1367-4803 |
| DOI: | 10.1093/bioinformatics/btg036 |
| Popis: | Motivation: The human genome project has led to the discovery of many human protein coding genes which were previously unknown. As a large fraction of these are functionally uncharacterized, it is of interest to develop methods for predicting their molecular function from sequence. Results: We have developed a method for prediction of protein function for a subset of classes from the Gene Ontology classification scheme. This subset includes several pharmaceutically interesting categories—transcription factors, receptors, ion channels, stress and immune response proteins, hormones and growth factors can all be predicted. Although the method relies on protein sequences as the sole input, it does not rely on sequence similarity, but instead on sequence derived protein features such as predicted post translational modifications (PTMs), protein sorting signals and physical/chemical properties calculated from the amino acid composition. This allows for prediction of the function for orphan proteins where no homologs can be found. Using this method we propose two novel receptors in the human genome, and further demonstrate chromosomal clustering of related proteins. Availability: Sequences can be submitted to the prediction server via a web interface at http://www.cbs.dtu.dk/services/ProtFun/ Contact: ljj@cbs.dtu.dk * To whom correspondence should be addressed. |
| Databáze: | OpenAIRE |
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