CapsEnhancer: An Effective Computational Framework for Identifying Enhancers Based on Chaos Game Representation and Capsule Network
Lantian Yao(Xiamen University), Tzong-Yi Lee(National Yang Ming Chiao Tung University), Yixian Huang(Chinese University of Hong Kong, Shenzhen), Ying‐Chih Chiang(Chinese University of Hong Kong, Shenzhen), Chia‐Ru Chung(National Central University), Yuxuan Pang(The University of Tokyo), Jiahui Guan(Chinese University of Hong Kong, Shenzhen), Peilin Xie(Chinese University of Hong Kong, Shenzhen), Huacong Wu(Chinese University of Hong Kong, Shenzhen)
Cited by 12
Related Papers
miRTarBase update 2022: an informative resource for experimentally validated miRNA–target interactions
|Nucleic Acids Research|2021|1k
dbAMP 2.0: updated resource for antimicrobial peptides with an enhanced scanning method for genomic and proteomic data
|Nucleic Acids Research|2021|179
dbPTM in 2022: an updated database for exploring regulatory networks and functional associations of protein post-translational modifications
|Nucleic Acids Research|2021|168
AVPIden: a new scheme for identification and functional prediction of antiviral peptides based on machine learning approaches
|Briefings in Bioinformatics|2021|91
CircNet 2.0: an updated database for exploring circular RNA regulatory networks in cancers
|Nucleic Acids Research|2021|77