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Single Nucleotide Polymorphism and Type 2 Diabetes Mellitus Phenotypes Association Using Gradient Boosting

机译:单核苷酸多态性与2型糖尿病表型关联使用梯度增强。

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Precision medicine is a medical field that aims to provide disease treatment according to an individual’s genetic information, environment and lifestyle. Recently, precision medicine researchs is focusing on studying complex diseases, such as diabetes mellitus (DM). The most common form of DM is type 2 DM (T2DM). T2DM patient’s genetic information can be obtained by finding an association between Single Nucleotide Polymorphism (SNP) and phenotypes of T2DM. This research aims to find SNPs which considered related to T2DM phenotypes using gradient boosting (GB) algorithm. Data were taken from Mouse Phenome Database website based on 98 protein candidates of T2DM. Preprocessing stage is conducted by deleting unused features and missing values, SNP encoding, and merging phenotypes and SNP data. Model was built using GB with decision tree base-learners and least square loss function. GB produced an average MSE value of 0.061 and MAE value of 0.171 and also obtained 30 SNPs that potentially associated with T2DM’s insulin tolerance phenotype. Twenty two of 30 choosen SNPs verified to have association with T2DM phenotypes on Mouse Genome Informatics website based on SNP-protein-phenotype relationship.
机译:精密医学是旨在根据个人的遗传信息,环境和生活方式提供疾病治疗的医学领域。近来,精密医学研究集中在研究复杂疾病,例如糖尿病(DM)。 DM的最常见形式是2型DM(T2DM)。通过发现单核苷酸多态性(SNP)与T2DM表型之间的关联,可以获得T2DM患者的遗传信息。这项研究旨在使用梯度增强(GB)算法找到被认为与T2DM表型有关的SNP。数据来自Mouse Phenome Database网站,基于98种T2DM候选蛋白质。通过删除未使用的特征和缺失值,SNP编码以及合并表型和SNP数据来进行预处理阶段。使用具有决策树基础学习者和最小二乘损失函数的GB构建模型。 GB产生的平均MSE值为0.061,MAE值为0.171,还获得了30个可能与T2DM胰岛素耐受性表型有关的SNP。根据SNP-蛋白质-表型关系,在小鼠基因组信息学网站上验证了30种选择的SNP中的22种与T2DM表型相关。

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