Applying graph database technology for analyzing perturbed co-expression networks in cancer.

ABSTRACT: Graph representations provide an elegant solution to capture and analyze complex molecular mechanisms in the cell. Co-expression networks are undirected graph representations of transcriptional co-behavior indicating (co-)regulations, functional modules or even physical interactions between the corresponding gene products. The growing avalanche of available RNA sequencing (RNAseq) data fuels the construction of such networks, which are usually stored in relational databases like most other biological data. Inferring linkage by recursive multiple-join statements, however, is computationally expensive and complex to design in relational databases. In contrast, graph databases store and represent complex interconnected data as nodes, edges and properties, making it fast and intuitive to query

SUBMITTER: Simpson CM 

PROVIDER: S-EPMC7731929 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature