New insights into protein-protein interaction data lead to increased estimates of the <it>S. cerevisiae </it>interactome size
<p>Abstract</p> <p>Background</p> <p>As protein interactions mediate most cellular mechanisms, protein-protein interaction networks are essential in the study of cellular processes. Consequently, several large-scale interactome mapping projects have been undertaken, and...
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doaj-403e9c01177d47a78e6766a7477157572020-11-24T23:44:14ZengBMCBMC Bioinformatics1471-21052010-12-0111160510.1186/1471-2105-11-605New insights into protein-protein interaction data lead to increased estimates of the <it>S. cerevisiae </it>interactome sizeThierry-Mieg NicolasSambourg Laure<p>Abstract</p> <p>Background</p> <p>As protein interactions mediate most cellular mechanisms, protein-protein interaction networks are essential in the study of cellular processes. Consequently, several large-scale interactome mapping projects have been undertaken, and protein-protein interactions are being distilled into databases through literature curation; yet protein-protein interaction data are still far from comprehensive, even in the model organism <it>Saccharomyces cerevisiae</it>. Estimating the interactome size is important for evaluating the completeness of current datasets, in order to measure the remaining efforts that are required.</p> <p>Results</p> <p>We examined the yeast interactome from a new perspective, by taking into account how thoroughly proteins have been studied. We discovered that the set of literature-curated protein-protein interactions is qualitatively different when restricted to proteins that have received extensive attention from the scientific community. In particular, these interactions are less often supported by yeast two-hybrid, and more often by more complex experiments such as biochemical activity assays. Our analysis showed that high-throughput and literature-curated interactome datasets are more correlated than commonly assumed, but that this bias can be corrected for by focusing on well-studied proteins. We thus propose a simple and reliable method to estimate the size of an interactome, combining literature-curated data involving well-studied proteins with high-throughput data. It yields an estimate of at least 37, 600 direct physical protein-protein interactions in <it>S. cerevisiae</it>.</p> <p>Conclusions</p> <p>Our method leads to higher and more accurate estimates of the interactome size, as it accounts for interactions that are genuine yet difficult to detect with commonly-used experimental assays. This shows that we are even further from completing the yeast interactome map than previously expected.</p> http://www.biomedcentral.com/1471-2105/11/605 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Thierry-Mieg Nicolas Sambourg Laure |
spellingShingle |
Thierry-Mieg Nicolas Sambourg Laure New insights into protein-protein interaction data lead to increased estimates of the <it>S. cerevisiae </it>interactome size BMC Bioinformatics |
author_facet |
Thierry-Mieg Nicolas Sambourg Laure |
author_sort |
Thierry-Mieg Nicolas |
title |
New insights into protein-protein interaction data lead to increased estimates of the <it>S. cerevisiae </it>interactome size |
title_short |
New insights into protein-protein interaction data lead to increased estimates of the <it>S. cerevisiae </it>interactome size |
title_full |
New insights into protein-protein interaction data lead to increased estimates of the <it>S. cerevisiae </it>interactome size |
title_fullStr |
New insights into protein-protein interaction data lead to increased estimates of the <it>S. cerevisiae </it>interactome size |
title_full_unstemmed |
New insights into protein-protein interaction data lead to increased estimates of the <it>S. cerevisiae </it>interactome size |
title_sort |
new insights into protein-protein interaction data lead to increased estimates of the <it>s. cerevisiae </it>interactome size |
publisher |
BMC |
series |
BMC Bioinformatics |
issn |
1471-2105 |
publishDate |
2010-12-01 |
description |
<p>Abstract</p> <p>Background</p> <p>As protein interactions mediate most cellular mechanisms, protein-protein interaction networks are essential in the study of cellular processes. Consequently, several large-scale interactome mapping projects have been undertaken, and protein-protein interactions are being distilled into databases through literature curation; yet protein-protein interaction data are still far from comprehensive, even in the model organism <it>Saccharomyces cerevisiae</it>. Estimating the interactome size is important for evaluating the completeness of current datasets, in order to measure the remaining efforts that are required.</p> <p>Results</p> <p>We examined the yeast interactome from a new perspective, by taking into account how thoroughly proteins have been studied. We discovered that the set of literature-curated protein-protein interactions is qualitatively different when restricted to proteins that have received extensive attention from the scientific community. In particular, these interactions are less often supported by yeast two-hybrid, and more often by more complex experiments such as biochemical activity assays. Our analysis showed that high-throughput and literature-curated interactome datasets are more correlated than commonly assumed, but that this bias can be corrected for by focusing on well-studied proteins. We thus propose a simple and reliable method to estimate the size of an interactome, combining literature-curated data involving well-studied proteins with high-throughput data. It yields an estimate of at least 37, 600 direct physical protein-protein interactions in <it>S. cerevisiae</it>.</p> <p>Conclusions</p> <p>Our method leads to higher and more accurate estimates of the interactome size, as it accounts for interactions that are genuine yet difficult to detect with commonly-used experimental assays. This shows that we are even further from completing the yeast interactome map than previously expected.</p> |
url |
http://www.biomedcentral.com/1471-2105/11/605 |
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