Abstract

Abstract The vast amount of experimental data from recent advances in the field of high-throughput biology begs for integration into more complex data structures such as genome-wide functional association networks. Such networks have been used for elucidation of the interplay of intra-cellular molecules to make advances ranging from the basic science understanding of evolutionary processes to the more translational field of precision medicine. The allure of the field has resulted in rapid growth of the number of available network resources, each with unique attributes exploitable to answer different biological questions. Unfortunately, the high volume of network resources makes it impossible for the intended user to select an appropriate tool for their particular research question. The aim of this paper is to provide an overview of the underlying data and representative network resources as well as to mention methods of integration, allowing a customized approach to resource selection. Additionally, this report will provide a primer for researchers venturing into the field of network integration.

Keywords

Computer scienceField (mathematics)Data scienceResource (disambiguation)Selection (genetic algorithm)Data integrationBiological networkState (computer science)Computational biologyArtificial intelligenceBiologyData miningComputer network

MeSH Terms

Computational BiologyDatabasesGeneticGenome

Affiliated Institutions

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Publication Info

Year
2019
Type
review
Volume
21
Issue
4
Pages
1224-1237
Citations
30
Access
Closed

Social Impact

Social media, news, blog, policy document mentions

Citation Metrics

30
OpenAlex
1
Influential
25
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Cite This

Dimitri Guala, Christoph Ogris, Nikola S. Müller et al. (2019). Genome-wide functional association networks: background, data & state-of-the-art resources. Briefings in Bioinformatics , 21 (4) , 1224-1237. https://doi.org/10.1093/bib/bbz064

Identifiers

DOI
10.1093/bib/bbz064
PMID
31281921
PMCID
PMC7373183

Data Quality

Data completeness: 90%