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Integrating gene expression and protein-protein interaction network to prioritize cancer-associated genes

机译:整合基因表达和蛋白质-蛋白质相互作用网络以区分癌症相关基因

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Background To understand the roles they play in complex diseases, genes need to be investigated in the networks they are involved in. Integration of gene expression and network data is a promising approach to prioritize disease-associated genes. Some methods have been developed in this field, but the problem is still far from being solved. Results In this paper, we developed a method, Networked Gene Prioritizer (NGP), to prioritize cancer-associated genes. Applications on several breast cancer and lung cancer datasets demonstrated that NGP performs better than the existing methods. It provides stable top ranking genes between independent datasets. The top-ranked genes by NGP are enriched in the cancer-associated pathways. The top-ranked genes by NGP-PLK1, MCM2, MCM3, MCM7, MCM10 and SKP2 might coordinate to promote cell cycle related processes in cancer but not normal cells. Conclusions In this paper, we have developed a method named NGP, to prioritize cancer-associated genes. Our results demonstrated that NGP performs better than the existing methods.
机译:背景技术为了了解它们在复杂疾病中的作用,需要在它们所涉及的网络中研究基因。基因表达和网络数据的整合是对疾病相关基因进行优先排序的一种有前途的方法。在该领域已经开发了一些方法,但是该问题仍未解决。结果在本文中,我们开发了一种网络基因优先级排序器(NGP)来对癌症相关基因进行优先级排序。在一些乳腺癌和肺癌数据集上的应用表明,NGP的性能优于现有方法。它在独立的数据集之间提供了稳定的顶级基因。 NGP中排名靠前的基因在癌症相关途径中富集。 NGP-PLK1,MCM2,MCM3,MCM7,MCM10和SKP2中排名靠前的基因可能会协同促进癌症中与细胞周期相关的过程,而不是正常细胞。结论在本文中,我们开发了一种名为NGP的方法来对癌症相关基因进行优先排序。我们的结果表明,NGP的性能优于现有方法。

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