The deluge of sequencing data needs curated association of structural and functional features to each sequence in the database. Inference of correct annotation is a major problem of sequence analysis. We highlight why it is difficult to solve the annotation task given the little amount of validated information in the database linking sequences, structure and experimental function in the most curated repository of protein sequences. We review state-of-the-art methods currently benchmarked in the Critical Assessment of protein Function Annotation algorithms (CAFA), an experiment designed to provide a large-scale assessment of computational methods dedicated to predicting protein function

Protein Functional Annotation

Pier Luigi Martelli;Giuseppe Profiti;Rita Casadio
2017

Abstract

The deluge of sequencing data needs curated association of structural and functional features to each sequence in the database. Inference of correct annotation is a major problem of sequence analysis. We highlight why it is difficult to solve the annotation task given the little amount of validated information in the database linking sequences, structure and experimental function in the most curated repository of protein sequences. We review state-of-the-art methods currently benchmarked in the Critical Assessment of protein Function Annotation algorithms (CAFA), an experiment designed to provide a large-scale assessment of computational methods dedicated to predicting protein function
2017
Reference Module in Life Sciences: Encyclopedia of Bioinformatics and Computational Biology
8
14
Pier Luigi Martelli; Giuseppe Profiti; Rita Casadio
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/906855
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