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Construction and Prediction of Protein-Protein Interaction Maps

Authors: V, Schächter;

Construction and Prediction of Protein-Protein Interaction Maps

Abstract

With the completion of full genome sequence for several model organisms, new approaches are emerging to comprehensively characterize the function of gene products. In these so-called functional proteomics approaches, large-scale assays on the complete set of proteins of a given organism — the proteome — enable the study of the function of proteins in their context, rather than individually. The recent emergence of high-throughput techniques to systematically identify physical interactions between proteins has opened new prospects. Not only can an important part of what is now referred to as the “function” of a protein be characterized more precisely through its interactions, but networks of interacting proteins also extend this purely local view of function by providing a first level of understanding of cellular mechanisms. In short, protein interaction maps can provide detailed functional insights on characterized as well as yet unannotated proteins, along with an information base for the identification of biological complexes and metabolic or signal transduction pathways (for review, see Walhout and Vidal 2001).

Keywords

Helicobacter pylori, Sequence Homology, Amino Acid, Molecular Sequence Data, Computational Biology, Proteins, Models, Biological, Protein Structure, Tertiary, Two-Hybrid System Techniques, Amino Acid Sequence, Dimerization, Algorithms, Software, Gene Library, Protein Binding

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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!
2
Average
Average
Average
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