换一批Evaluating the detection ability of a range of epistasis detection methods on simulated data for pure and impure epistatic models.
第一作者：
Dominic,Russ
第一单位：
Institute of Cancer and Genomic Sciences, Centre for Computational Biology, University of Birmingham, Birmingham, United Kingdom.;Institute of Translational Medicine, University of Birmingham, Birmingham, United Kingdom.
作者：
医学主题词
算法(Algorithms);等位基因(Alleles);心房颤动(Atrial Fibrillation);数据挖掘(Data Mining);肌营养不良蛋白相关蛋白质类(Dystrophin-Associated Proteins);上位性, 遗传(Epistasis, Genetic);基因频率(Gene Frequency);基因座(Genetic Loci);全基因组关联研究(Genome-Wide Association Study);基因型(Genotype);人类(Humans);线性模型(Linear Models);微丝蛋白质类(Microfilament Proteins);模型, 遗传学(Models, Genetic);多因子降维法(Multifactor Dimensionality Reduction);神经组织蛋白质类(Nerve Tissue Proteins);神经肽类(Neuropeptides);外显率(Penetrance);多态性, 单核苷酸(Polymorphism, Single Nucleotide);ROC曲线(ROC Curve)
DOI
10.1371/journal.pone.0263390
PMID
35180244
发布时间
2023-07-06
- 浏览0
PloS one
e0263390页
相似文献
- 中文期刊
- 外文期刊
- 学位论文
- 会议论文
