Preprint
Leveraging User-Friendly Network Approaches to Extract Knowledge From High-Throughput Omics Datasets
Registro en:
RAMOS, Pablo Ivan Pereira et al. Leveraging user-friendly network approaches to extract knowledge from high-throughput omics datasets. Frontiers in Genetics, v. 10, p. 1-51, 2019.
10.3389/fgene.2019.01120
Autor
Ramos, Pablo Ivan Pereira
Arge, Luis Willian Pacheco
Lima, Nicholas Costa Barroso
Fukutani, Kiyoshi Ferreira
Queiroz, Artur Trancoso Lopo de
Resumen
Conselho Nacional de Desenvolvimento Científico e
Tecnológico (CNPq), Brazil [Universal 28/2018; grant protocol 427183/2018-9]. LA
received a postdoctoral fellowship from the Coordenação de Aperfeiçoamento de Pessoal de
725 Nível Superior (CAPES). AQ acknowledges funding from Fundação Oswaldo Cruz (INOVA
- Process VPPIS-001-FIO-18-45). Publication fees were defrayed by Fundação Oswaldo
Cruz. The funders had no role in study design, analysis, decision to publish, or preparation of
the manuscript 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.