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Activity Number: 76
Type: Contributed
Date/Time: Sunday, July 31, 2016 : 4:00 PM to 5:50 PM
Sponsor: Section on Statistics in Genomics and Genetics
Abstract #321451
Title: XTalk: A Path-Based Approach for Identifying Crosstalk Between Signaling Pathways
Author(s): Allison Tegge* and T. M. Murali and Nicholas Sharp
Companies: and Virginia Tech and Virginia Tech
Keywords: crosstalk ; pathway analysis ; systems biology ; network analysis
Abstract:

Cells communicate with their environment via signal transduction pathways. On occasion, the activation of one pathway can produce an effect downstream of another pathway, a phenomenon known as crosstalk. We developed XTalk, a path-based approach for identifying pairs of pathways that may crosstalk. XTalk computes short paths that connect receptors in one pathway to the transcription factors in another. XTalk uses a dynamic program to exactly compute the statistical significance of the average length of these paths. By design, XTalk reports networks that include the precise interactions and mechanisms that support the identified crosstalk. We compared XTalk to two existing approaches using a set of known pathways that crosstalk. XTalk achieved an area under the ROC curve (AUC) of 0.65, a 12% improvement over the closest competing approach. We found support in the literature for 60% of the false positives, both among pathways with low AUCs and among highly-ranked pairs. Additionally, we provide examples of networks computed by XTalk that accurately recovered known mechanisms of crosstalk.


Authors who are presenting talks have a * after their name.

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