A Framework Integrating Heterogeneous Databases for the Completion of Gene Networks

IEEE Access

Ying Ju¹  Han Luo¹  Donghua Wang²  Juan Liu³  Zhe Jin⁴ 

[1] Department of Computer Science, School of Informatics, Xiamen University, Xiamen, China;Department of General Surgery, Heilongjiang Province Land Reclamation Headquarters General Hospital, Harbin, China;Department of Instrument and Electrical Engineering, School of Aerospace Engineering, Xiamen University, Xiamen, China;School of Information Technology, Monash University Malaysia, Subang Jaya, Malaysia;

关键词: Neural integration;    matrix completion;    heterogeneous networks;    gene interaction prediction;    optimization;    reconstruction;   

DOI  :  10.1109/ACCESS.2019.2954994

来源: DOAJ

【 摘 要 】

Molecular networks embraced diverse biological and functional associations between genes and gene products, which are conducive for identifying novel genes and pathways of a specific disease phenotype. Although great progress has been achieved in high-throughput interactome mapping, the associations among genes still incomplete which caused the sparsity of Gene Networks (GNs). Here, we proposed a network-based framework, termed NIHO, for optimizing and completing GNs by integrating six genome networks: STRING, ConsenusPathDB, HumanNet, GeneMANIA, GIANT and BioGRID. NIHO learns high-level features of genes from the heterogeneous networks by an end-to-end way that consisted of neural network and matrix completion. Then, the learned low-dimensional representations are used to calculate the geometric proximity of genes in the projected space. Finally, NIHO infers the interactions among genes by analyzing the proximity scores and adds those interactions that originally not existed into GNs. The experimental results showed that the capability of GNs to recover disease gene sets get significantly improved after processed by NIHO. In addition, we not only examined the proportion of the added interactions but also observed the performance of NIHO can be promoted when the number of heterogeneous networks is increased.

【 授权许可】

Unknown