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BioMed Research International
Volume 2015, Article ID 301635, 9 pages
http://dx.doi.org/10.1155/2015/301635
Research Article

A Network Flow Approach to Predict Protein Targets and Flavonoid Backbones to Treat Respiratory Syncytial Virus Infection

1Centro Infant, Pontifical Catholic University of Rio Grande do Sul (PUCRS), Avenue Ipiranga 6681, 90619-900 Porto Alegre, RS, Brazil
2Clinical Research Center, Hospital Israelita Albert Einstein (HIAE), São Paulo, Brazil
3Department of Molecular Biology and Biotechnology, Federal University of Rio Grande do Sul (UFRGS), 90619-900 Porto Alegre, RS, Brazil
4Faculty of Informatics, Laboratory for Bioinformatics, Modelling & Simulation of Biosystems, Pontifical Catholic University of Rio Grande do Sul (PUCRS), 90619-900 Porto Alegre, RS, Brazil

Received 26 July 2014; Accepted 11 September 2014

Academic Editor: Jiangning Song

Copyright © 2015 José Eduardo Vargas et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Supplementary Material

Supplementary figure 1: All PPI networks obtained in this work. PPI network was obtained from microarrays data of PHBE cells infected with RSV, and flavonoid compounds, as initial input of STITCH software.

Supplementary Table 1: All gene ontologies obtanied from major PPI network through.

Supplementary Table 2: CentiScape Analysis. (a) Degree, betweeness and closeness centrality scores of each node in RSV CP-PPI network. (b) Hub (H) and bottlenecks (B) nodes are showed with their closeness values.

  1. Supplementary Materials