The molecular mechanisms underlying tissue regeneration and wound healing are still poorly understood despite their importance. In this paper we develop a bioinformatics approach, combining biology and network theory to drive experiments for better understanding the genetic underpinnings of wound healing mechanisms and for selecting potential drug targets. We start by selecting literature-relevant genes in murine wound healing, and inferring from them a Protein-Protein Interaction (PPI) network. Then, we analyze the network to rank wound healing-related genes according to their topological properties. Lastly, we perform a procedure for in-silico simulation of a treatment action in a biological pathway. The findings obtained by applying the developed pipeline, including gene expression analysis, confirms how a network-based bioinformatics method is able to prioritize candidate genes for in vitro analysis, thus speeding up the understanding of molecular mechanisms and supporting the discovery of potential drug targets.
| Identifer | oai:union.ndltd.org:arizona.edu/oai:arizona.openrepository.com:10150/626101 |
| Date | 21 June 2017 |
| Creators | Vitali, Francesca, Marini, Simone, Balli, Martina, Grosemans, Hanne, Sampaolesi, Maurilio, Lussier, Yves, Cusella De Angelis, Maria, Bellazzi, Riccardo |
| Contributors | Univ Arizona Hlth Sci, Ctr Biomed Informat & Biostat, Univ Arizona, Inst Ctr Biomed Informat & Biostat BIO5, Univ Arizona, Dept Med |
| Publisher | MDPI AG |
| Source Sets | University of Arizona |
| Language | English |
| Detected Language | English |
| Type | Article |
| Rights | © 2017 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license. |
| Relation | http://www.mdpi.com/1424-8247/10/2/55 |
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