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Bioinformatics
Article . 2007 . Peer-reviewed
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Bioinformatics
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Bioinformatics
Article . 2007
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Comparison of human protein–protein interaction maps

Authors: Matthias E. Futschik; Gautam Chaurasia; Hanspeter Herzel;

Comparison of human protein–protein interaction maps

Abstract

AbstractMotivation: Large-scale mappings of protein–protein interactions have started to give us new views of the complex molecular mechanisms inside a cell. After initial projects to systematically map protein interactions in model organisms such as yeast, worm and fly, researchers have begun to focus on the mapping of the human interactome. To tackle this enormous challenge, different approaches have been proposed and pursued. While several large-scale human protein interaction maps have recently been published, their quality remains to be critically assessed.Results: We present here a first comparative analysis of eight currently available large-scale maps with a total of over 10 000 unique proteins and 57 000 interactions included. They are based either on literature search, orthology or by yeast-two-hybrid assays. Comparison reveals only a small, but statistically significant overlap. More importantly, our analysis gives clear indications that all interaction maps imply considerable selection and detection biases. These results have to be taken into account for future assembly of the human interactome.Availability: An integrated human interaction network called Unified Human Interactome (UniHI) is made publicly accessible at http://www.mdc-berlin.de/unihi.Contact: m.futschik@biologie.hu-berlin.deSupplementary information: Supplementary data are available at Bioinformatics online.

Keywords

Proteomics, Protein Interaction Mapping, Computational Biology, Humans, Proteins, Databases, Protein

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
73
Top 10%
Top 10%
Top 1%
gold