A comprehensive assessment of long intrinsic protein disorder from the DisProt database
Author(s) -
Marco Necci,
Damiano Piovesan,
Zsuzsanna Dosztányi,
Péter Tompa,
Silvio C. E. Tosatto
Publication year - 2017
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btx590
Subject(s) - benchmarking , computer science , benchmark (surveying) , ranking (information retrieval) , data mining , database , raw data , annotation , reference database , proxy (statistics) , uniprot , set (abstract data type) , information retrieval , machine learning , artificial intelligence , biology , biochemistry , geodesy , marketing , gene , business , programming language , geography
Intrinsic disorder (ID), i.e. the lack of a unique folded conformation at physiological conditions, is a common feature for many proteins, which requires specialized biochemical experiments that are not high-throughput. Missing X-ray residues from the PDB have been widely used as a proxy for ID when developing computational methods. This may lead to a systematic bias, where predictors deviate from biologically relevant ID. Large benchmarking sets on experimentally validated ID are scarce. Recently, the DisProt database has been renewed and expanded to include manually curated ID annotations for several hundred new proteins. This provides a large benchmark set which has not yet been used for training ID predictors.
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