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Pharmaceuticals 2017, 10(2), 55; doi:10.3390/ph10020055

Exploring Wound-Healing Genomic Machinery with a Network-Based Approach

Center for Biomedical Informatics and Biostatistics, The University of Arizona Health Sciences, Tucson, AZ 85721, USA
BIO5 Institute Center for Biomedical Informatics and Biostatistics, The University of Arizona, Tucson, AZ 85721, USA
Department of Medicine, The University of Arizona, Tucson, AZ 85721, USA
Department of Electrical, Computer and Biomedical Engineering, University of Pavia, Pavia 27100, Italy
Centre for Health Technologies, University of Pavia, Pavia 27100, Italy
Department of Development and Regeneration, Laboratory of Translational Cardiomyology, KULeuven, 3000 Leuven, Belgium
Department of Public Health, Experimental and Forensic Medicine, Institute of Human Anatomy, University of Pavia, Pavia 27100, Italy
Istituti Clinici Scientifici Maugeri, Pavia 27100, Italy
Author to whom correspondence should be addressed.
Academic Editor: Simona Collina
Received: 11 May 2017 / Revised: 13 June 2017 / Accepted: 14 June 2017 / Published: 21 June 2017
(This article belongs to the Special Issue Tissue-Protective Agents: New Drugs and Technologies)
View Full-Text   |   Download PDF [7550 KB, uploaded 21 June 2017]   |  


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. View Full-Text
Keywords: network pharmacology; gene prioritization; wound healing network pharmacology; gene prioritization; wound healing

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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. (CC BY 4.0).

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MDPI and ACS Style

Vitali, F.; Marini, S.; Balli, M.; Grosemans, H.; Sampaolesi, M.; Lussier, Y.A.; Cusella De Angelis, M.G.; Bellazzi, R. Exploring Wound-Healing Genomic Machinery with a Network-Based Approach. Pharmaceuticals 2017, 10, 55.

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