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A novel SVM-ID3 Hybrid Feature Selection Method to Build a Disease Model for Melanoma using Integrated Genotyping and Phenotype Data from dbGaP

机译：一种新的SVM-ID3混合特征选择方法，用于使用DBGAP的集成基因分型和表型数据构建黑色素瘤的疾病模型

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The relations between Single Nucleotide Polymorphism (SNP) and complex diseases are likely to be non-linear and require analysis of the high dimensional data. Previous studies in the field mostly focus on genotyping and effects of various phenotypes are not considered. To fill this gap a hybrid feature selection model of support vector machine and decision tree has been designed. The designed method is tested on melanoma. We were able to select phenotypic features such as moles and dysplastic nevi, and SNPs those maps to specific genes such as CAMK1D. The performance results of the proposed hybrid model, on melanoma dataset are 79.07% of sensitivity and 0.81 of area under ROC curve.

机译：单核苷酸多态性（SNP）和复杂疾病之间的关系可能是非线性的并且需要分析高尺寸数据。以前在该领域的研究主要关注各种表型的基因分型，并且不考虑各种表型的影响。为了填充此间隙，设计了支持向量机和决策树的混合特征选择模型。设计方法对黑色素瘤进行了测试。我们能够选择摩尔斯和消化骨质骨骼的表型特征，并将这些地图SNPS与诸如Camk1d等特定基因的映射。拟议的杂种模型的性能结果，黑素瘤数据集的灵敏度为79.07％，曲线下面积为0.81。

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《European Federation for Medical Informatics., Conference》|2014年||共5页
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Yesim Aydin SON; Sait Can YUCEBAS;
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1. Text Categorization of Heart, Lung, and Blood Studies in the Database of Genotypes and Phenotypes (dbGaP) Utilizing n-grams and Metadata Features: [J] . Mindy K. Ross, Ko-Wei Lin, Karen Truong, Biomedical Informatics Insights . 2013,第1期

机译：利用n-gram和元数据功能对基因型和表型（dbGaP）数据库中的心脏，肺和血液研究进行文本分类：
2. Text Categorization of Heart, Lung, and Blood Studies in the Database of Genotypes and Phenotypes (dbGaP) Utilizing n-grams and Metadata Features: [J] . Mindy K. Ross, Ko-Wei Lin, Karen Truong, Biomedical Informatics Insights . 2013,第1期

机译：利用n-gram和元数据功能对基因型和表型（dbGaP）数据库中的心脏，肺和血液研究进行文本分类：
3. NCBI's Database of Genotypes and Phenotypes: dbGaP [J] . Anne Sturcke, Kimberly A. Tryka, Lora Ziyabari, Nucleic acids research . 2014,第D1期

机译：NCBI基因型和表型数据库：dbGaP
4. A novel SVM-ID3 Hybrid Feature Selection Method to Build a Disease Model for Melanoma using Integrated Genotyping and Phenotype Data from dbGaP [C] . Yesim Aydin SON, Sait Can YUCEBAS European Federation for Medical Informatics., Conference . 2014

机译：一种新的SVM-ID3混合特征选择方法，用于使用DBGAP的集成基因分型和表型数据构建黑色素瘤的疾病模型
5. Predictive Modeling of Human Disease: Comparison of Genome-Wide Phenotype Prediction Methods, a Method for Novel Genetic Feature Coding, and Development of Biomarkers for Freidreich Ataxia [D] . Zhao, Zoe Zijun. 2019

机译：人类疾病预测建模：基因组宽表型预测方法的比较，一种新型遗传特征编码的方法，以及弗赖德德希共济失调的生物标志物的发展
6. Correction: A Prostate Cancer Model Build by a Novel SVM-ID3 Hybrid Feature Selection Method Using Both Genotyping and Phenotype Data from dbGaP [O] . -1

机译：校正：使用来自dbGaP的基因分型和表型数据的新型SVM-ID3混合特征选择方法构建的前列腺癌模型
7. A prostate cancer model build by a novel SVM-ID3 hybrid feature selection method using both genotyping and phenotype data from dbGaP. [O] . Sait Can Yücebaş, Yeşim Aydın Son 2014

机译：通过使用来自dbGap的基因分型和表型数据的新型sVm-ID3杂交特征选择方法构建前列腺癌模型。

A novel SVM-ID3 Hybrid Feature Selection Method to Build a Disease Model for Melanoma using Integrated Genotyping and Phenotype Data from dbGaP

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