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. 2021 Feb 24;10:627701. doi: 10.3389/fonc.2020.627701

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Copyright © 2021 Malik, Thanekar, Amarachintha, Mourya, Nalluri, Bondoc and Shivakumar

This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

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Protein-protein interaction network analysis identifies biological relatedness of complement components to regulators of hepatocellular carcinoma (HCC) pathogenesis. Complement molecules of relevance to HCC were subjected to protein-protein interaction (PPI) network analysis using the network-based gene prioritization algorithm, ToppGenet of the ToppGene Suite (http://toppgene.cchmc.org). ToppGenet identifies and prioritizes candidate genes based on functional annotations, similar expressions, and network and topographical features. A Step Size of 6 and the Prioritization method of k-Step Markov were used as default analytical parameters. The Cytoscape-compatible ToppGenet output file was used to generate the graphical network. The first shell of 41 interacting proteins (grey color) associated directly with the input complement proteins (blue) in the PPI were generated by Cytoscape.