Sequence-based feature prediction and annotation of proteins

被引：0
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作者：
Agnieszka S Juncker
Lars J Jensen
Andrea Pierleoni
Andreas Bernsel
Michael L Tress
Peer Bork
Gunnar von Heijne
Alfonso Valencia
Christos A Ouzounis
Rita Casadio
Søren Brunak
机构：
[1] Technical University of Denmark,Center for Biological Sequence Analysis, Department of Systems Biology
[2] European Molecular Biology Laboratory,Center for Biomembrane Research and Stockholm Bioinformatics Center, Department of Biochemistry and Biophysics
[3] University of Bologna,KCL Centre for Bioinformatics
[4] Biocomputing Group,undefined
[5] Stockholm University,undefined
[6] Structural Biology and Biocomputing Programme,undefined
[7] Spanish National Cancer Research Centre (CNIO),undefined
[8] School of Physical Sciences and Engineering,undefined
[9] King's College London,undefined
来源：
Genome Biology | / 10卷
关键词：
Gene Ontology; Additional Data File; Linear Motif; Membrane Protein Structure; Computational Annotation;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
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.
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