Leveraging User-Friendly Network Approaches to Extract Knowledge From High-Throughput Omics Datasets

Ramos, Pablo Ivan Pereira and Arge, Luis Willian Pacheco and Lima, Nicholas Costa Barroso and Fukutani, Kiyoshi F. and de Queiroz, Artur Trancoso L. (2019) Leveraging User-Friendly Network Approaches to Extract Knowledge From High-Throughput Omics Datasets. Frontiers in Genetics, 10. ISSN 1664-8021

[thumbnail of pubmed-zip/versions/1/package-entries/fgene-10-01120.pdf] Text
pubmed-zip/versions/1/package-entries/fgene-10-01120.pdf - Published Version

Download (2MB)

Abstract

Recent technological advances for the acquisition of multi-omics data have allowed an unprecedented understanding of the complex intricacies of biological systems. In parallel, a myriad of computational analysis techniques and bioinformatics tools have been developed, with many efforts directed towards the creation and interpretation of networks from this data. In this review, we begin by examining key network concepts and terminology. Then, computational tools that allow for their construction and analysis from high-throughput omics datasets are presented. We focus on the study of functional relationships such as co-expression, protein–protein interactions, and regulatory interactions that are particularly amenable to modeling using the framework of networks. We envisage that many potential users of these analytical strategies may not be completely literate in programming languages and code adaptation, and for this reason, emphasis is given to tools’ user-friendliness, including plugins for the widely adopted Cytoscape software, an open-source, cross-platform tool for network analysis, visualization, and data integration.

Item Type: Article
Subjects: Lib Research Guardians > Medical Science
Depositing User: Unnamed user with email support@lib.researchguardians.com
Date Deposited: 30 Jan 2023 10:44
Last Modified: 29 Jul 2024 05:42
URI: http://eprints.classicrepository.com/id/eprint/93

Actions (login required)

View Item
View Item