Reference: Suthram S, et al. (2006) A direct comparison of protein interaction confidence assignment schemes. BMC Bioinformatics 7:360

Reference Help

Abstract


BACKGROUND: Recent technological advances have enabled high-throughput measurements of protein-protein interactions in the cell, producing large protein interaction networks for various species at an ever-growing pace. However, common technologies like yeast two-hybrid may experience high rates of false positive detection. To combat false positive discoveries, a number of different methods have been recently developed that associate confidence scores with protein interactions. Here, we perform a rigorous comparative analysis and performance assessment among these different methods. RESULTS: We measure the extent to which each set of confidence scores correlates with similarity of the interacting proteins in terms of function, expression, pattern of sequence conservation, and homology to interacting proteins in other species. We also employ a new metric, the Signal-to-Noise Ratio of protein complexes embedded in each network, to assess the power of the different methods. Seven confidence assignment schemes, including those of Bader et al., Deane et al., Deng et al., Sharan et al., and Qi et al., are compared in this work. CONCLUSION: Although the performance of each assignment scheme varies depending on the particular metric used for assessment, we observe that Deng et al. yields the best performance overall (in three out of four viable measures). Importantly, we also find that utilizing any of the probability assignment schemes is always more beneficial than assuming all observed interactions to be true or equally likely.

Reference Type
Comparative Study | Journal Article | Research Support, N.I.H., Extramural | Research Support, Non-U.S. Gov't
Authors
Suthram S, Shlomi T, Ruppin E, Sharan R, Ideker T
Primary Lit For
Additional Lit For
Review For

Interaction Annotations


Increase the total number of rows showing on this page by using the pull-down located below the table, or use the page scroll at the table's top right to browse through the table's pages; use the arrows to the right of a column header to sort by that column; filter the table using the "Filter" box at the top of the table; click on the small "i" buttons located within a cell for an annotation to view further details about experiment type and any other genes involved in the interaction.

Interactor Interactor Type Assay Annotation Action Modification Phenotype Source Reference

Gene Ontology Annotations


Increase the total number of rows showing on this page using the pull-down located below the table, or use the page scroll at the table's top right to browse through the table's pages; use the arrows to the right of a column header to sort by that column; filter the table using the "Filter" box at the top of the table.

Gene Qualifier Gene Ontology Term Aspect Annotation Extension Evidence Method Source Assigned On Reference

Phenotype Annotations


Increase the total number of rows showing on this page using the pull-down located below the table, or use the page scroll at the table's top right to browse through the table's pages; use the arrows to the right of a column header to sort by that column; filter the table using the "Filter" box at the top of the table; click on the small "i" buttons located within a cell for an annotation to view further details.

Gene Phenotype Experiment Type Mutant Information Strain Background Chemical Details Reference

Disease Annotations


Increase the total number of rows showing on this page using the pull-down located below the table, or use the page scroll at the table's top right to browse through the table's pages; use the arrows to the right of a column header to sort by that column; filter the table using the "Filter" box at the top of the table.

Gene Disease Ontology Term Qualifier Evidence Method Source Assigned On Reference

Regulation Annotations


Increase the total number of rows displayed on this page using the pull-down located below the table, or use the page scroll at the table's top right to browse through the table's pages; use the arrows to the right of a column header to sort by that column; to filter the table by a specific experiment type, type a keyword into the Filter box (for example, “microarray”); download this table as a .txt file using the Download button or click Analyze to further view and analyze the list of target genes using GO Term Finder, GO Slim Mapper, SPELL, or YeastMine.

Regulator Target Direction Regulation Of Happens During Method Evidence