Exploring Wound-Healing Genomic Machinery with a Network-Based Approach.
Exploring Wound-Healing Genomic Machinery with a Network-Based Approach.
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DOI：
10.3390/ph10020055
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发表时间：
2017-06-21
期刊：
影响因子：
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通讯作者：
Bellazzi R
中科院分区：
文献类型：
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作者：
Vitali F;Marini S;Balli M;Grosemans H;Sampaolesi M;Lussier YA;Cusella De Angelis MG;Bellazzi R
组织再生和伤口愈合的分子机制尽管重要，但仍然知之甚少。在本文中，我们开发了一种生物信息学方法，结合生物学和网络理论来驱动实验，以更好地了解伤口愈合机制的遗传基础，并选择潜在的药物靶点。我们首先选择文献相关的基因在小鼠伤口愈合，并推断从他们的蛋白质-蛋白质相互作用（PPI）网络。然后，我们分析网络，根据它们的拓扑特性对伤口愈合相关基因进行排序。最后，我们执行一个程序，在生物途径中的治疗行动的计算机模拟。通过应用开发的管道（包括基因表达分析）获得的发现证实了基于网络的生物信息学方法如何能够优先考虑体外分析的候选基因，从而加快对分子机制的理解并支持潜在药物靶点的发现。
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.