BACKGROUND Cancer as a kind of genomic alteration disease each year deprives many people's life. The biggest challenge to overcome cancer is to identify driver genes that promote the cancer development from a huge amount of passenger mutations that have no effect on the selective growth advantage of cancer. In order to solve those problems, some researchers have started to focus on identification of driver genes by integrating networks with other biological information. However, more efforts should be needed to improve the prediction performance. METHODS Considering the facts that driver genes have impact on expression of their downstream genes, they likely interact with each other to form functional modules and those modules should tend to be expressed similarly in the same tissue. We proposed a novel model named by DyTidriver to identify driver genes through involving the gene dysregulated expression, tissue-specific expression and variation frequency into the human functional interaction network (e.g. human FIN). RESULTS This method was applied on 974 breast, 316 prostate and 230 lung cancer patients. The consequence shows our method outperformed other five existing methods in terms of Fscore, Precision and Recall values. The enrichment and cociter analysis illustrate DyTidriver can not only identifies the driver genes enriched in some significant pathways but also has the capability to figure out some unknown driver genes. CONCLUSION The final results imply that driver genes are those that impact more dysregulated genes and express similarly in the same tissue.

中文翻译：

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识别涉及基因失调表达，组织特异性表达和基因-基因网络的驱动基因。

背景技术癌症每年作为一种基因组改变疾病剥夺了许多人的生命。克服癌症的最大挑战是从大量的乘客突变中识别出促进癌症发展的驱动基因，而这些突变对癌症的选择性生长优势没有影响。为了解决这些问题，一些研究人员已经开始集中精力通过将网络与其他生物学信息整合在一起来鉴定驱动基因。但是，需要付出更多的努力来改善预测性能。方法考虑到驱动基因对其下游基因表达有影响的事实，它们可能彼此相互作用形成功能模块，并且那些模块应该倾向于在同一组织中相似地表达。我们提出了一种以DyTidriver命名的新型模型，该模型通过将基因失调的表达，组织特异性表达和变异频率纳入人类功能相互作用网络（例如人类FIN）来识别驱动基因。结果该方法应用于974名乳腺癌，316名前列腺癌和230名肺癌患者。结果表明，在Fscore，Precision和Recall值方面，我们的方法优于其他五个现有方法。富集和亲子分析表明，DyTidriver不仅可以识别在某些重要途径中富集的驱动基因，而且还具有找出某些未知驱动基因的能力。结论最终结果暗示驱动基因是那些影响更多失调基因并在同一组织中相似表达的基因。