title: Identifying ion channel genes related to cardiomyopathy using a novel decision forest strategy.
abstract: Ion channels play many crucial functions in life. Their dysfunction may lead to a number of diseases, such as arrhythmia and beta cell dysfunction. In this study, we firstly selected the ion channel gene expression profiles using a dimensionality reduction method. After that, we applied a novel decision forest strategy to mine cardiomyopathy related ion channel genes. The novel proposed Zi integrated the information of the decision trees' height and the frequency at which a gene was located in the tree. It achieved a much higher ability of feature selection. In the result, 26 cardiomyopathy related ion channel genes were identified. Their Zi were higher than the threshold Z*. Furthermore, most of these genes had been reported to have relationships with cardiomyopathies. In conclusion, our proposed decision forest strategy had a better classification performance. Our result can provide a theoretical basis for cardiovascular researchers.
authors: Department of Prevention, Tongji University School of Medicine, Shanghai, China. jiezhang@tongji.edu.cn jueli@tongji.edu.cn.
authors: Jie
authors: J
authors: Zhang
authors: Guanghua
authors: G
authors: Wang
authors: Jian
authors: J
authors: Feng
authors: LiJuan
authors: L
authors: Zhang
authors: Jue
authors: J
authors: Li
mesh_terms: D000465:Algorithms; D009202:Cardiomyopathies / Q000235:genetics*; D003663:Decision Trees; D020869:Gene Expression Profiling / Q000379:methods; D006801:Humans; D007473:Ion Channels / Q000235:genetics*; D059467:Transcriptome / Q000235:genetics
chemical_list: D007473:Ion Channels