PFP/ESG: automated protein function prediction servers enhanced with Gene Ontology visualization tool

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PFP/ESG: automated protein function prediction servers enhanced with Gene Ontology visualization tool

UNLABELLED Protein function prediction (PFP) is an automated function prediction method that predicts Gene Ontology (GO) annotations for a protein sequence using distantly related sequences and contextual associations of GO terms. Extended similarity group (ESG) is another GO prediction algorithm that makes predictions based on iterative sequence database searches. Here, we provide interactive ...

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Prediction of human protein function according to Gene Ontology categories

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 Ontol...

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Gene function prediction with knowledge from gene ontology

Gene function prediction is an important problem in bioinformatics. Due to the inherent noise existing in the gene expression data, the attempt to improve the prediction accuracy resorting to new classification techniques is limited. With the emergence of Gene Ontology (GO), extra knowledge about the gene products can be extracted from GO and facilitates solving the gene function prediction pro...

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PFP: Automated prediction of gene ontology functional annotations with confidence scores using protein sequence data.

Protein function prediction is a central problem in bioinformatics, increasing in importance recently due to the rapid accumulation of biological data awaiting interpretation. Sequence data represents the bulk of this new stock and is the obvious target for consideration as input, as newly sequenced organisms often lack any other type of biological characterization. We have previously introduce...

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ژورنال

عنوان ژورنال: Bioinformatics

سال: 2014

ISSN: 1460-2059,1367-4803

DOI: 10.1093/bioinformatics/btu646