Sequence-based feature prediction and annotation of proteins

doi:10.1186/gb-2009-10-2-206

Genome Biology

Volume 10
Issue 2

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Juncker AS
Jensen LJ
Pierleoni A
Bernsel A
Tress ML
Bork P
von Heijne G
Valencia A
Ouzounis CA
Casadio R
Brunak S

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Juncker AS
Jensen LJ
Pierleoni A
Bernsel A
Tress ML
Bork P
von Heijne G
Valencia A
Ouzounis CA
Casadio R
Brunak S
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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

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

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

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

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

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

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

author email corresponding author email

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


Published:	2 February 2009

Subject areas: Biochemistry and structural biology, Bioinformatics, Genome studies, Methods, Molecular biology

Abstract

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.