论文标题
使用基因在人类调节网络中检测驱动基因检测的网络科学方法会影响评估
A Network Science Approach to Driver Gene Detection In Human Regulatory Network Using Genes Influence Evaluation
论文作者
论文摘要
癌症疾病是由于细胞调节机制中的疾病而引起的，导致细胞畸形。开始畸形的基因称为癌症驱动基因（CDG）。已经引入了许多计算方法来识别使用突变概念的癌症驱动基因。在人类细胞和肿瘤发育中传播的异常，CDG可能是网络中具有很高影响的基因的潜在基因类型。这增加了影响CDG鉴定的影响扩散概念的重要性。基于影响最大化鉴定癌症驱动基因的影响。这些类型网络的挑战之一是找到边缘之间的调节相互作用的力量。当前的研究开发了一种识别癌症驱动基因并预测调节性相互作用在转录调节网络中的影响的技术。该技术利用了影响扩散的概念，并根据影响扩散优化了超链接引起的主题搜索算法。结果表明，与其他基于计算和网络的方法相比，我们提出的技术的性能更好。
Cancer disease occurs because of a disorder in the cellular regulatory mechanism, Which causes cellular malformation. The genes that start the malformation are called Cancer driver genes (CDGs) . Numerous computational methods have been introduced to identify cancer driver genes that use the concept of mutation.Regarding abnormalities spread in human cell and tumor development, CDGs are likely to be the potential types of gene with high influence in the network. This increases the importance of influence diffusion concept for the identification of CDGs.recently developed a method based on influence maximization for identifying cancer driver genes. One of the challenges in these types of networks is to find the power of regulatory interaction between edges.The current study developed a technique to identify cancer driver gene and predict the impact of regulatory interactions in a transcriptional regulatory network. This technique utilizes the concept of influence diffusion and optimizes the Hyperlink-Induced Topic Search algorithm based on the influence diffusion. The results suggest the better performance of our proposed technique than the other computational and network-based approaches.
