Musso G, et al. (2011) Filtering and interpreting large-scale experimental protein-protein interaction data. Methods Mol Biol 781():295-309
Abstract: Rarely acting in isolation, it is invariably the physical associations among proteins that define their biological activity, necessitating the study of the cellular meshwork of protein-protein interactions (PPI) before a full appreciation of gene function can be achieved. The past few years have seen a marked expansion in the both the sheer volume and number of organisms for which high-quality interaction data is available, with high-throughput interaction screening and detection techniques showing consistent improvement both in scale and sensitivity. Although techniques for large-scale PPI mapping are increasingly being applied to new organisms, including human, there is a corresponding need to rigorously evaluate, benchmark, and impartially filter the results. This chapter explores methods for PPI dataset evaluation, including a survey of previous techniques applied by landmark studies in the field and a discussion of promising new experimental approaches. We further outline practical suggestions and useful tools for interpreting newly generated PPI data. As the majority of large-scale experimental data has been generated for the budding yeast S. cerevisiae, most of the techniques and datasets described are from the perspective of this model unicellular eukaryote; however, extensions to other organisms including mammals are mentioned where possible.
|Status: Published||Type: Journal Article||PubMed ID: 21877287|
Topics addressed in this paper
- To find other papers on a gene and topic, click on the colored ball in the appropriate box.
- displays other papers with information about that topic for that gene.
- displays other papers in SGD that are associated with that topic.
The topic is addressed in these papers but does not describe a specific gene or chromosomal feature.
- To go to the Locus page for a gene, click on the gene name.