We are analyzing https://link.springer.com/article/10.1186/1471-2105-5-116.

Title:
Applying Support Vector Machines for Gene ontology based gene function prediction | BMC Bioinformatics
Description:
Background The current progress in sequencing projects calls for rapid, reliable and accurate function assignments of gene products. A variety of methods has been designed to annotate sequences on a large scale. However, these methods can either only be applied for specific subsets, or their results are not formalised, or they do not provide precise confidence estimates for their predictions. Results We have developed a large-scale annotation system that tackles all of these shortcomings. In our approach, annotation was provided through Gene Ontology terms by applying multiple Support Vector Machines (SVM) for the classification of correct and false predictions. The general performance of the system was benchmarked with a large dataset. An organism-wise cross-validation was performed to define confidence estimates, resulting in an average precision of 80% for 74% of all test sequences. The validation results show that the prediction performance was organism-independent and could reproduce the annotation of other automated systems as well as high-quality manual annotations. We applied our trained classification system to Xenopus laevis sequences, yielding functional annotation for more than half of the known expressed genome. Compared to the currently available annotation, we provided more than twice the number of contigs with good quality annotation, and additionally we assigned a confidence value to each predicted GO term. Conclusions We present a complete automated annotation system that overcomes many of the usual problems by applying a controlled vocabulary of Gene Ontology and an established classification method on large and well-described sequence data sets. In a case study, the function for Xenopus laevis contig sequences was predicted and the results are publicly available at ftp://genome.dkfz-heidelberg.de/pub/agd/gene_association.agd_Xenopus .
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Keywords {🔍}

terms, annotation, sequences, gene, function, sequence, number, article, term, pubmed, google, scholar, confidence, classifiers, ontology, relationship, databases, training, precision, hits, attributes, cas, prediction, molecular, data, test, tigr, values, figure, annotated, system, xenopus, organisms, path, yeast, fly, applied, query, set, cdna, accuracy, votes, coverage, functional, quality, predictions, classification, protein, bioinformatics, average,

Topics {✒️}

tw/~cjlin/libsvm/index uk/ebi_docs/swissprot_db/swisshome nationales genom-forschungs-netz organism-wise cross-validation approach support vector machines de/pub/agd/gene_association johannes gutenberg-universität mainz tigr gene indices organism-wise cross-validation org/tdb/tgi article download pdf coral del val grid search determined large-scale protein annotation sequencing projects calls full size image gene ontology consortium cdna sequencing projects large-scale annotation system privacy choices/manage cookies gene ontology guideline gene ontology resource gene ontology categories full access authors’ original file describe gene products gene ontology annotation gene ontology graph machine learning algorithms machine learning strategy gene function finding fold cross validation xenopus laevis sequences orthologous gene displacement gene association files biomed central gene association tables high-quality manual annotation falk schubert roland eils grid search computational functional assignment article vinayagam gene ontology terms full size table related subjects display endopeptidase activity prolyl aminopeptidase activity high-quality manual annotations molecular function ontology

Questions {❓}

Bork P, Koonin EV: Predicting function from protein sequence: Where are the bottlenecks?

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      name:Department of Molecular Biophysics, Deutsches Krebsforschungszentrum (DKFZ), Heidelberg, Germany
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      name:Theoretical Bioinformatics, Deutsches Krebsforschungszentrum (DKFZ), TP3, Heidelberg, Germany
      name:Theoretical Bioinformatics, Deutsches Krebsforschungszentrum (DKFZ), TP3, Heidelberg, Germany
      name:Department of Molecular Biophysics, Deutsches Krebsforschungszentrum (DKFZ), Heidelberg, Germany
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