Abstract
The integration of heterogeneous biological data into a common network representation is of paramount importance in different areas of biology and medicine. The size of the generated network in many cases prevents the possibility of its graphical visualization, inspection, and identification of characteristics. In this paper, we present the main features of UNIPred-Web (UNIPred-Web is available at https://unipred.di.unimi.it/), a web application realized to support the user in the integration of several biomolecular networks and for their visualization and navigation at different resolution levels. In particular, the identification and effective visualization of hierarchical communities allow an easy exploration of the entire network, while protein function prediction functionalities support the user in the interpretation process.
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References
Franz, M., et al.: GeneMANIA update 2018. Nucleic Acids Res. 46(W1), W06–W64 (2018)
Frasca, M., et al.: UNIPred: unbalance-aware network integration and prediction of protein functions. J. Comput. Biol. 22(12), 1057–1074 (2015)
Frasca, M., Valentini, G.: COSNet: an R package for label prediction in unbalanced biological networks. Neurocomputing 237, 397–400 (2017)
Gordon, D.E., et al.: A SARS-CoV-2 protein interaction map reveals targets for drug repurposing. Nature 583(7816), 459–468 (2020)
Perlasca, P., et al.: Multi-resolution visualization and analysis of biomolecular networks through hierarchical community detection and web-based graphical tools. PLoS ONE 15(12), e0244241 (2020)
Perlasca, P., et al.: UNIPred-Web: a web tool for the integration and visualization of biomolecular networks for protein function prediction. BMC Bioinform. 20(1), 1–19 (2019). https://doi.org/10.1186/s12859-019-2959-2
Szklarczyk, D., et al.: STRING v11: protein-protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets. Nucleic Acids Res. 47(D1), D607–D613 (2018)
Wong, A.K., et al.: IMP 2.0: a multi-species functional genomics portal for integration, visualization and prediction of protein functions and networks. Nucleic Acids Res. 43, W128–W133 (2015)
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Perlasca, P. et al. (2023). Integration and Visual Analysis of Biomolecular Networks Through UNIPred-Web. In: Agapito, G., et al. Current Trends in Web Engineering. ICWE 2022. Communications in Computer and Information Science, vol 1668. Springer, Cham. https://doi.org/10.1007/978-3-031-25380-5_15
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DOI: https://doi.org/10.1007/978-3-031-25380-5_15
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