Open Badges Review

Sequence-based feature prediction and annotation of proteins

Agnieszka S Juncker1, Lars J Jensen2, Andrea Pierleoni3, Andreas Bernsel4, Michael L Tress5, Peer Bork2, Gunnar von Heijne4, Alfonso Valencia5, Christos A Ouzounis6, Rita Casadio3 and Søren Brunak1*

Author Affiliations

1 Center for Biological Sequence Analysis, Department of Systems Biology, Technical University of Denmark, DK-2800 Lyngby, Denmark

2 European Molecular Biology Laboratory, D-69117 Heidelberg, Germany

3 University of Bologna, Biocomputing Group, Via San Giacomo 9/2, 40126 Bologna, Italy

4 Center for Biomembrane Research and Stockholm Bioinformatics Center, Department of Biochemistry and Biophysics, Stockholm University, SE-106 91 Stockholm, Sweden

5 Structural Biology and Biocomputing Programme, Spanish National Cancer Research Centre (CNIO), Melchor Fernández Almagro, 3, E-28029, Madrid, Spain

6 KCL Centre for Bioinformatics, School of Physical Sciences and Engineering, King's College London, London WC2R 2LS, UK

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Genome Biology 2009, 10:206  doi:10.1186/gb-2009-10-2-206

Published: 2 February 2009


A recent trend in computational methods for annotation of protein function is that many prediction tools are combined in complex workflows and pipelines to facilitate the analysis of feature combinations, for example, the entire repertoire of kinase-binding motifs in the human proteome.