Sequence-based feature prediction and annotation of proteins

被引：0

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.

引用

共 50 条

[1] Sequence-based feature prediction and annotation of proteins
Juncker, Agnieszka S.
Jensen, Lars J.
Pierleoni, Andrea
Bernsel, Andreas
Tress, Michael L.
Bork, Peer
von Heijne, Gunnar
Valencia, Alfonso
Ouzounis, Christos A.
Casadio, Rita
Brunak, Soren
[J]. GENOME BIOLOGY, 2009, 10 (02): : 206
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