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UniHI


NAR Molecular Biology Database Collection entry number 960
Futschik, Matthias; Kalathur, Ravi; Pinto, José; Hernandez-Prieto, Miguel; Machado, Rui; Chaurasia, Gautam
1Institute for Theoretical Biology, Charité, Humboldt University, Berlin, Germany
2Max Delbrück Center for Molecular Medicine, Berlin-Buch, Germany
3Center of Molecular and Structural Biomedicine, University of Algarve, Faro, Portugal

Database Description

Systematic mapping of protein-protein interactions (PPIs) has become a central task of functional genomics. To map the human interactome, several strategies have recently been pursued. The generated interaction datasets are valuable resources for scientists in biology and medicine. However, comparison reveals limited overlap between different interaction networks. This divergence obstructs usability, as researchers have to interrogate numerous heterogeneous datasets to identify potential interaction partners for proteins of interest. To facilitate direct access through a single entry gate, we have started to integrate currently available human protein interaction data in an easily accessible online database, called UniHI (Unified Human Interactome).
UniHI provides researchers with a flexible integrated tool for the exploration of the human interactome. It enables the assembly of comprehensive lists of protein interactions and flexible network-orientated searching. Network structures can be identified which would not be detectable if single maps were analyzed separately. For highly targeted search, UniHI offers several tools to specify the displayed interactions. Also, scores for quality assessment are given based on co-annotation and co-expression of the interacting proteins. Various hyperlinks to other databases facilitate users to follow-up results retrieved in UniHI.

Recent Developments

Since its first release, UniHI has considerably increased in size. The latest update of UniHI (version 4) includes over 250,000 interactions between ~22,300 unique proteins collected from 14 major PPI sources. However, this wealth of data also poses new challenges for researchers due to the complexity of interaction networks retrieved from the database. We therefore developed several new tools to query, analyze and visualize human PPI networks.
While the former versions of UniHI only provided non-interactive display, the present update includes interactive graphical tools which offer many attractive features for rapid analysis and adjustment of the extracted information. Most importantly, UniHI allows now the focused querying of canonical pathways and construction of tissue-specific interaction networks: The UniHI Pathway Scanner provides the possibility to examine the intersection of canonical pathways from KEGG with the extracted networks. In this way, it enables researchers to detect possible modifiers of pathways as well as proteins involved in the cross-talk between different pathways. An additional new tool termed UniHI Express allows the filtering of PPIs based on gene expression in selected tissues and thus enables the construction of tissue-specific networks and represents a first step towards a dynamic representation of the human interactome.
UniHI will continue to extend its scope by the incorporation of newly available PPI resources and to consolidate the frequently divergent data. In this context, we like to invite other data providers and researchers to participate in the UniHI project.

Acknowledgements

We would like to acknowledge the support of the German BMBF (NGFN2, KB-P04T03, 01GR0471) and the Deutsche Forschungsgemeinschaft (DFG) by the SFB 618 grant.

References

1. Gautam Chaurasia, Yasir Iqbal, Christian Hänig, Hanspeter Herzel, Erich E. Wanker and Matthias E. Futschik (2007) UniHI: An Entry Gate to the Human Protein Interactome. Nucleic Acids Res. 35: in press.


Go to the abstract in the NAR 2014 Database Issue.
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