Bioinformatics | Protein Folding | Theory & Simulation | Structural Genomics
A community resource for analysis and understanding of intrinsic disorder in proteins of fully sequenced genomes
Matt Oates*, Pedro Romero, Takashi Ishida, Mohamed Ghalwash, Vladimir Uversky, Bin Xue, Zoran Obradovic, Keith Dunker, Julian Gough
*Corresponding author: Matt Oates
Computer Science, University of Bristol, Bristol, UK
F1000Posters 2012, 3: 974 (poster) [English]
Poster [4.03 MB]
Presented at
International Conference on Intelligent Systems for Molecular Biology (ISMB) 2012,
14 - 16 Jul 2012, W36
We present a community resource for pre-computed protein disorder predictions over a large library of known amino acid sequences. Goals of the database include making statistical comparisons of the various prediction methods freely available to the prediction community, as well as facilitating biological investigation of the disordered protein space. The database consists of 12,314,806 sequences in 1,765 complete genomes from 1,256 distinct species.
Disorder is currently predicted by five different disorder predictors, with 2,055 SCOP structural domains predicted by SUPERFAMILY included for comparison with disorder.
Disorder adds considerable coverage to the amino acid space when included in addition to structural domain assignments. Protein disorder affects a large portion of the protein annotation produced from genome research so is important for any thorough study of protein content.
No relevant competing interests disclosed.
EPSRC, EP/E501214/1
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