Negatome 2.0: a database of non-interacting proteins derived by literature mining, manual annotation and protein structure analysis.
Knowledge about non-interacting proteins (NIPs) is important for training the algorithms to predict protein-protein interactions (PPIs) and for assessing the false positive rates of PPI detection efforts. We present the second version of Negatome, a database of proteins and protein domains that are unlikely to engage in physical interactions (available online at http://mips.helmholtz-muenchen.de/proj/ppi/negatome). Negatome is derived by manual curation of literature and by analyzing three-dimensional structures of protein complexes. The main methodological innovation in Negatome 2.0 is the utilization of an advanced text mining procedure to guide the manual annotation process. Potential non-interactions were identified by a modified version of Excerbt, a text mining tool based on semantic sentence analysis. Manual verification shows that nearly a half of the text mining results with the highest confidence values correspond to NIP pairs. Compared to the first version the contents of the database have grown by over 300%.
Institute for Bioinformatics and Systems Biology/MIPS, HMGU - German Research Center for Environmental Health, Ingolstaedter Landstrasse 1, 85764 Neuherberg, Germany, Clueda AG, Elsenheimerstraße 59, 80687 Munich, Germany and Department of Genome Oriented Bioinformatics, Technische Universitaet Muenchen Wissenschaftszentrum Weihenstephan, 85350 Freising, Germany.
Philipp
P
Blohm
Goar
G
Frishman
Pawel
P
Smialowski
Florian
F
Goebels
Benedikt
B
Wachinger
Andreas
A
Ruepp
Dmitrij
D
Frishman
D057225:Data Mining; D030562:Databases, Protein; D020407:Internet; D058977:Molecular Sequence Annotation; D011487:Protein Conformation; D054730:Protein Interaction Domains and Motifs; D025941:Protein Interaction Mapping