Gene expression data classification using topology and machine learning models

被引:0
作者
Tamal K. Dey
Sayan Mandal
Soham Mukherjee
机构
[1] Purdue University,Department of Computer Science
[2] The Ohio State University,Department of Computer Science and Engineering
来源
BMC Bioinformatics | / 22卷
关键词
Topological data analysis; Gene expression; Persistent cycles; Neural network;
D O I
暂无
中图分类号
学科分类号
摘要
引用
收藏
相关论文
共 109 条
[1]  
Cang Z(2017)Topologynet: topology based deep convolutional and multi-task neural networks for biomolecular property predictions PLoS Comput Biol 13 1-27
[2]  
Wei G-W(2018)Topological data analysis quantifies biological nano-structure from single molecule localization microscopy bioRxiv 95 14863-14868
[3]  
Pike JA(2019)Topological data analysis reveals principles of chromosome structure throughout cellular differentiation bioRxiv 10 38316-369
[4]  
Khan AO(1998)Cluster analysis and display of genome-wide expression patterns Proc Natl Acad Sci 4 339-7270
[5]  
Pallini C(2016)Clustering algorithms: their application to gene expression data Bioinform Biol Insights 108 7265-13
[6]  
Thomas SG(2019)A topological data analysis network model of asthma based on blood gene expression profiles bioRxiv 9 13-159
[7]  
Mund M(2015)Identification of copy number aberrations in breast cancer subtypes using persistence topology Microarrays 18 151-426
[8]  
Ries J(2011)Topology based data analysis identifies a subgroup of breast cancers with a unique mutational profile and excellent survival Proc Natl Acad Sci 8 16477-21
[9]  
Poulter NS(2008)A comparative study of different machine learning methods on microarray gene expression data BMC Genom 15 1006826-1182
[10]  
Styles IB(2017)Gene expression based cancer classification Egypt Inform J 47 419-2830