Aggregated network centrality shows non-random structure of genomic and proteomic networks
Abstract
Network analysis is a powerful tool for modelling biological systems. We propose a new approach that integrates the genomic interaction data at population level with the proteomic interaction data. In our approach we use chromatin interaction analysis by paired-end tag sequencing (ChIA-PET) data from human genome to construct a set of genomic interaction networks, considering the natural partitioning of chromatin into chromatin contact domains...
Paper Details
Title
Aggregated network centrality shows non-random structure of genomic and proteomic networks
Published Date
Oct 1, 2020
Journal
Volume
181-182
Pages
5 - 14
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