基于多目标评价方法的乳腺癌易感基因排序及其网络表达研究

目的利用已有的研究结果和数据，采用多目标评价方法建立乳腺癌易感基因评价模型，对与已知乳腺癌基因关系密切的其它基因进行分析和排序，并给出结果的网络表达模式。方法通过分析已有的文献，并利用有关的基因数据库和已有文献中的数据，提炼出乳腺癌易感基因的多目标评价体系，构建基于加权和法的乳腺癌易感基因评价模型，并利用Cytoscape软件进行评价结果计算和评价结果的网络模式表达。结果利用多目标模型所得到的评价结果，与已有的研究结果一致。其中，乳腺癌易感基因TopBP1排名第二，已知乳腺癌候选易感基因HMMR排名第六。结论文章提出的多目标评价模型能够准确评价被选基因与乳腺癌易感性之间的关系，所提出的评价方法与相关软件结合使用，将成为癌症易感基因研究方面有效的分析方法和途径。

Gene Ranking and Network Expression Modeling of Breast Cancer Susceptible Genes on the Basis of Multi-Criteria Evaluation

Objective Based on previous results and data, this paper was proposed to establish an evaluation model by means of multi-criteria evaluation, in order to analyze and rank breast cancer susceptible genes which are known to be closely related to breast cancer genes and provide their network expression model. Methods By analysis of available literatures and by use of gene database, we selected the evaluation criteria for identifying breast cancer susceptible genes and then set up the evaluation model using the data from online supplementary table provided by literatures and gene database. After that, the evaluation results and their network expression were processed using Cytoscape software. Results The obtained gene ranking results from our multi-criteria model were consistent with previous researches. In this model, the breast cancer susceptible gene TopBP1 was secondly ranked, and the HMMR gene, a known candidate of breast cancer susceptible gene, was ranked at the sixth position. Conclusion s Our established multi-evaluation model can objectively and correctly represent the complex relationship between genes and breast cancer susceptibility. In combination with relative software programs, this method is a potent tool for biomedical analysis.