Details

Autor(en) / Beteiligte

• Koskinen, Patrik
• Törönen, Petri
• Nokso-Koivisto, Jussi
• Holm, Liisa

Titel

PANNZER: high-throughput functional annotation of uncharacterized proteins in an error-prone environment

Ist Teil von

• Bioinformatics, 2015-05, Vol.31 (10), p.1544-1552

Ort / Verlag

England

Erscheinungsjahr

2015

Quelle

MEDLINE

Beschreibungen/Notizen

• The last decade has seen a remarkable growth in protein databases. This growth comes at a price: a growing number of submitted protein sequences lack functional annotation. Approximately 32% of sequences submitted to the most comprehensive protein database UniProtKB are labelled as 'Unknown protein' or alike. Also the functionally annotated parts are reported to contain 30-40% of errors. Here, we introduce a high-throughput tool for more reliable functional annotation called Protein ANNotation with Z-score (PANNZER). PANNZER predicts Gene Ontology (GO) classes and free text descriptions about protein functionality. PANNZER uses weighted k-nearest neighbour methods with statistical testing to maximize the reliability of a functional annotation. Our results in free text description line prediction show that we outperformed all competing methods with a clear margin. In GO prediction we show clear improvement to our older method that performed well in CAFA 2011 challenge.