Comparison of tissue disease specific integrated networks using directed graphlet signatures

Date

2016-10-05

Author

SÖNMEZ, ARZU BURÇAK
Can, Tolga

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We present a novel framework for counting small sub-graph patterns in integrated genome-scale networks. An integrated network was built using the physical, regulatory, and metabolic interactions between H. sapiens proteins from the Pathway Commons database. The network was filtered for tissue/disease specific proteins by using a large-scale human transcriptional profiling study, resulting in several tissue and disease specific sub-networks. In this study, we apply and extend the idea of graphlet counting in undirected protein-protein interaction (PPI) networks to directed multi-labeled networks and represent each network as a vector of graphlet counts. Graphlet counts are assessed for statistical significance by comparison against a set of randomized networks. We present our results on analysis of differential graphlets between different conditions. Our results show that graphlets can be used for identification of systems level differences between disease states.

Subject Keywords

integrated networks, network comparison, directed graphlet

URI

https://hdl.handle.net/11511/68831

DOI

https://doi.org/10.1145/2975167.2985674

Collections

Department of Computer Engineering, Conference / Seminar

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Citation Formats

A. B. SÖNMEZ and T. Can, “Comparison of tissue disease specific integrated networks using directed graphlet signatures,” 2016, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/68831.