| URL: | http://www.compbio.dundee.ac.uk/www-pips/ |
| Full name: | human protein–protein interaction prediction database |
| Description: | PIPs is a database of predicted human protein-protein interactions. The predictions are generated by combination of experimental evidence for interactions integrated within a naive Bayes framework. The database provides full details on the evidence for each predicted interaction. |
| Year founded: | 2009 |
| Last update: | 2009-01-01 |
| Version: | v1.0 |
| Accessibility: |
Accessible
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| Country/Region: | United Kingdom |
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| University/Institution: | University of Dundee |
| Address: | Dow Street, Dundee, DD1 5EH, UK |
| City: | Dundee |
| Province/State: | |
| Country/Region: | United Kingdom |
| Contact name (PI/Team): | Geoffrey J. Barton |
| Contact email (PI/Helpdesk): | gjbarton@dundee.ac.uk |
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PIPs: human protein-protein interaction prediction database. [PMID: 18988626]
The PIPs database (http://www.compbio.dundee.ac.uk/www-pips) is a resource for studying protein-protein interactions in human. It contains predictions of >37,000 high probability interactions of which >34,000 are not reported in the interaction databases HPRD, BIND, DIP or OPHID. The interactions in PIPs were calculated by a Bayesian method that combines information from expression, orthology, domain co-occurrence, post-translational modifications and sub-cellular location. The predictions also take account of the topology of the predicted interaction network. The web interface to PIPs ranks predictions according to their likelihood of interaction broken down by the contribution from each information source and with easy access to the evidence that supports each prediction. Where data exists in OPHID, HPRD, DIP or BIND for a protein pair this is also reported in the output tables returned by a search. A network browser is included to allow convenient browsing of the interaction network for any protein in the database. The PIPs database provides a new resource on protein-protein interactions in human that is straightforward to browse, or can be exploited completely, for interaction network modelling. |