The KUPNetViz: a biological network viewer for multiple -omics datasets in kidney diseases

Abstract

BackgroundConstant technological advances have allowed scientists in biology to migrate from conventional single-omics to multi-omics experimental approaches, challenging bioinformatics to bridge this multi-tiered information. Ongoing research in renal biology is no exception. The results of large-scale and/or high throughput experiments, presenting a wealth of information on kidney disease are scattered across the web. To tackle this problem, we recently presented the KUPKB, a multi-omics data repository for renal diseases.ResultsIn this article, we describe KUPNetViz, a biological graph exploration tool allowing the exploration of KUPKB data through the visualization of biomolecule interactions. KUPNetViz enables the integration of multi-layered experimental data over different species, renal locations and renal diseases to protein-protein interaction networks and allows association with biological functions, biochemical pathways and other functional elements such as miRNAs. KUPNetViz focuses on the simplicity of its usage and the clarity of resulting networks by reducing and/or automating advanced functionalities present in other biological network visualization packages. In addition, it allows the extrapolation of biomolecule interactions across different species, leading to the formulations of new plausible hypotheses, adequate experiment design and to the suggestion of novel biological mechanisms. We demonstrate the value of KUPNetViz by two usage examples: the integration of calreticulin as a key player in a larger interaction network in renal graft rejection and the novel observation of the strong association of interleukin-6 with polycystic kidney disease.ConclusionsThe KUPNetViz is an interactive and flexible biological network visualization and exploration tool. It provides renal biologists with biological network snapshots of the complex integrated data of the KUPKB allowing the formulation of new hypotheses in a user friendly manner.

Inflammation-Related Mechanisms in Chronic Kidney Disease Prediction, Progression, and Outcome

“…CKD273 has recently received a letter of support from the US Food and Drug Administration (FDA), being now implemented in the CKD management [ 154 ]. Furthermore, CKD databases have been created; thus, KUPNetViz represents an interactive and flexible biological network tool for multiomics datasets, in the field of kidney diseases, providing biological network snapshots of the complex integrated data of the KUPKB (Kidney and Urinary Pathway Knowledge Base), thus creating the premises of generating novel in silico theories [ 155 ]. Furthermore, a CKD database (CKDdb) has been developed due to the vast amount of data generated by using high-throughput omics technologies.…”

A Hybrid Computational Method for the Discovery of Novel Reproduction-Related Genes

“…Thus, these interactions include physical and functional associations of proteins, which therefore widely measure the relationship between proteins and are different from experimentally determined PPIs provided in some other databases, such as DIP (Database of Interaction Proteins) database [ 40 ], BioGRID [ 41 ], etc . This kind of PPIs has been applied to investigate some protein-related problems [ 35 – 37 , 42 – 44 ]. We extracted 1,640,707 PPIs of human from the obtained file, where 86,854 are validated by solid experiments.…”

Omics databases on kidney disease: where they can be found and how to benefit from them

“…The Kidney and Urinary Pathway Knowledge Base (KUPKB) is a web tool that includes data from different omics datasets on kidney diseases and facilitates rapid hypothesis generation in the context of renal pathophysiology in a simple environment [ 42 ]. The KUPKB offers the network visualization tool KUPNetViz, which enables users to integrate multilayered experimental data over different species, renal locations and renal diseases and protein–protein interaction networks and identify associations with biological functions, biochemical pathways and other functional elements such as miRNAs [ 43 ]. In a recent publication, Sanchez-Nino et al [ 44 ] examined the role of the brain abundant signal protein 1 (BASP1) in albumin-induced tubular cell death and its correlation with CKD.…”