CONSTRUCTION AND ANALYSIS OF TISSUE/DISEASE SPECIFIC PROTEIN-PROTEIN INTERACTION NETWORKS BY INTEGRATING LARGE SCALE TRANSCRIPTOME DATA WITH GENOME SCALE PROTEIN-PROTEIN INTERACTION NETWORKS

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2022-7-25

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SÖNMEZ, ARZU BURÇAK

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Analysis of integrated genome-scale networks is a challenging problem due to heterogeneity of high-throughput data. There are several topological measures, such as graphlet counts and degree distributions, for characterization of biological networks. In this dissertation, we present methods for counting graphlet patterns in integrated genome-scale networks which are modeled as labeled multidigraphs. We have obtained physical, regulatory, and metabolic interactions between H. sapiens proteins from the Pathway Commons database. For the first part of the dissertation, the integrated network is filtered for tissue/disease specific proteins by using a large-scale human transcriptional profiling study, resulting in several tissue and disease specific sub-networks. We have applied and extended the idea of graphlet counting in undirected protein-protein interaction (PPI) networks to directed multi-labeled networks and represented 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 and on the utility of graphlet count vectors for clustering multiple condition specific networks. Our results show that there are numerous statistically significant graphlets in integrated biological networks and the graphlet signature vector can be used as an effective representation of a multilabeled network for clustering and systems level analysis of tissue/disease specific networks. The second part of the dissertation provides methods for comparing the network nodes based on the counts of 3- and 4-node multilabeled graphlets starting from these nodes. Then, we use different types of cancer pathways to retrieve the integrated interactions occurring between them from Pathway Commons dataset. These interactions are further investigated for identifying recurring 3- and 4-node graphlet patterns and Pathway Commons dataset and on different cancer pathways.

Subject Keywords

Integrated Networks, Network Comparison, ,Directed Graphlets, Systems Biology

URI

https://hdl.handle.net/11511/98588

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Graduate School of Informatics, Thesis

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Citation Formats

A. B. SÖNMEZ, “CONSTRUCTION AND ANALYSIS OF TISSUE/DISEASE SPECIFIC PROTEIN-PROTEIN INTERACTION NETWORKS BY INTEGRATING LARGE SCALE TRANSCRIPTOME DATA WITH GENOME SCALE PROTEIN-PROTEIN INTERACTION NETWORKS,” Ph.D. - Doctoral Program, Middle East Technical University, 2022.