Please use this identifier to cite or link to this item:
|Title:||Gene network interconnectedness and the generalized topological overlap measure||Authors:||Yip, A.M.
|Issue Date:||2007||Citation:||Yip, A.M., Horvath, S. (2007). Gene network interconnectedness and the generalized topological overlap measure. BMC Bioinformatics 8 : -. ScholarBank@NUS Repository. https://doi.org/10.1186/1471-2105-8-22||Abstract:||Background: Network methods are increasingly used to represent the interactions of genes and/or proteins. Genes or proteins that are directly linked may have a similar biological function or may be part of the same biological pathway. Since the information on the connection (adjacency) between 2 nodes may be noisy or incomplete, it can be desirable to consider alternative measures of pairwise interconnectedness. Here we study a class of measures that are proportional to the number of neighbors that a pair of nodes share in common. For example, the topological overlap measure by Ravasz et al. 1 can be interpreted as a measure of agreement between the m = 1 step neighborhoods of 2 nodes. Several studies have shown that two proteins having a higher topological overlap are more likely to belong to the same functional class than proteins having a lower topological overlap. Here we address the question whether a measure of topological overlap based on higher-order neighborhoods could give rise to a more robust and sensitive measure of interconnectedness. Results: We generalize the topological overlap measure from m = 1 step neighborhoods to m ≥ 2 step neighborhoods. This allows us to define the m-th order generalized topological overlap measure (GTOM) by (i) counting the number of m-step neighbors that a pair of nodes share and (ii) normalizing it to take a value between 0 and 1. Using theoretical arguments, a yeast co-expression network application, and a fly protein network application, we illustrate the usefulness of the proposed measure for module detection and gene neighborhood analysis. Conclusion: Topological overlap can serve as an important filter to counter the effects of spurious or missing connections between network nodes. The m-th order topological overlap measure allows one to trade-off sensitivity versus specificity when it comes to defining pairwise interconnectedness and network modules. © 2007 Yip and Horvath; licensee BioMed Central Ltd.||Source Title:||BMC Bioinformatics||URI:||http://scholarbank.nus.edu.sg/handle/10635/103321||ISSN:||14712105||DOI:||10.1186/1471-2105-8-22|
|Appears in Collections:||Staff Publications|
Show full item record
Files in This Item:
There are no files associated with this item.
checked on May 26, 2023
WEB OF SCIENCETM
checked on May 26, 2023
checked on May 25, 2023
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.