Negatome


24214996	Negatome 2.0: a database of non-interacting proteins derived by literature mining, manual annotation and protein structure analysis. [PMID: 24214996] Blohm P, Frishman G, Smialowski P, Goebels F, Wachinger B, Ruepp A, Frishman D. Abstract 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%. Nucleic Acids Res. 2014:42(Database issue) \| 78 Citations (from Europe PMC, 2025-03-29)
19920129	The Negatome database: a reference set of non-interacting protein pairs. [PMID: 19920129] Smialowski P, Pagel P, Wong P, Brauner B, Dunger I, Fobo G, Frishman G, Montrone C, Rattei T, Frishman D, Ruepp A. Abstract The Negatome is a collection of protein and domain pairs that are unlikely to be engaged in direct physical interactions. The database currently contains experimentally supported non-interacting protein pairs derived from two distinct sources: by manual curation of literature and by analyzing protein complexes with known 3D structure. More stringent lists of non-interacting pairs were derived from these two datasets by excluding interactions detected by high-throughput approaches. Additionally, non-interacting protein domains have been derived from the stringent manual and structural data, respectively. The Negatome is much less biased toward functionally dissimilar proteins than the negative data derived by randomly selecting proteins from different cellular locations. It can be used to evaluate protein and domain interactions from new experiments and improve the training of interaction prediction algorithms. The Negatome database is available at http://mips.helmholtz-muenchen.de/proj/ppi/negatome. Nucleic Acids Res. 2010:38(Database issue) \| 68 Citations (from Europe PMC, 2025-03-29)

Negatome 2.0: a database of non-interacting proteins derived by literature mining, manual annotation and protein structure analysis. [PMID: 24214996]

Blohm P, Frishman G, Smialowski P, Goebels F, Wachinger B, Ruepp A, Frishman D.

Abstract

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%.

Nucleic Acids Res. 2014:42(Database issue) | 78 Citations (from Europe PMC, 2025-03-29)

The Negatome database: a reference set of non-interacting protein pairs. [PMID: 19920129]

Smialowski P, Pagel P, Wong P, Brauner B, Dunger I, Fobo G, Frishman G, Montrone C, Rattei T, Frishman D, Ruepp A.

Abstract

The Negatome is a collection of protein and domain pairs that are unlikely to be engaged in direct physical interactions. The database currently contains experimentally supported non-interacting protein pairs derived from two distinct sources: by manual curation of literature and by analyzing protein complexes with known 3D structure. More stringent lists of non-interacting pairs were derived from these two datasets by excluding interactions detected by high-throughput approaches. Additionally, non-interacting protein domains have been derived from the stringent manual and structural data, respectively. The Negatome is much less biased toward functionally dissimilar proteins than the negative data derived by randomly selecting proteins from different cellular locations. It can be used to evaluate protein and domain interactions from new experiments and improve the training of interaction prediction algorithms. The Negatome database is available at http://mips.helmholtz-muenchen.de/proj/ppi/negatome.

Nucleic Acids Res. 2010:38(Database issue) | 68 Citations (from Europe PMC, 2025-03-29)

URL:	http://mips.helmholtz-muenchen.de/proj/ppi/negatome/
Full name:	The Negatome Database
Description:	A database of non-interacting proteins derived by literature mining,manual annotation and protein structure analysis
Year founded:	2010
Last update:	2013-11-08
Version:	v2.0
Accessibility:	Accessible
Country/Region:	Germany

Data type:	Protein
Data object:	NA
Database category:	Structure
Major species:	NA
Keywords:	non-interacting protein

University/Institution:	German Research Center for Environmental Health
Address:	Ingolstaedter Landstrasse 1,85764 Neuherberg,Germany
City:	Neuherberg
Province/State:
Country/Region:	Germany
Contact name (PI/Team):	Dmitrij Frishman
Contact email (PI/Helpdesk):	d.frishman@wzw.tum.de

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Database Commons a catalog of worldwide biological databases