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Bioinformatics advances in eccDNA identification and analysis.
Li, Fuyu; Ming, Wenlong; Lu, Wenxiang; Wang, Ying; Dong, Xianjun; Bai, Yunfei.
Affiliation
  • Li F; State Key Laboratory of Digital Medical Engineering, School of Biological Science and Medical Engineering, Southeast University, Nanjing, 210096, PR China.
  • Ming W; Institute for AI in Medicine, School of Artificial Intelligence, Nanjing University of Information Science and Technology, Nanjing, 210044, PR China. wming@nuist.edu.cn.
  • Lu W; State Key Laboratory of Digital Medical Engineering, School of Biological Science and Medical Engineering, Southeast University, Nanjing, 210096, PR China.
  • Wang Y; State Key Laboratory of Digital Medical Engineering, School of Biological Science and Medical Engineering, Southeast University, Nanjing, 210096, PR China.
  • Dong X; Adams Center of Parkinson's Disease Research, Yale School of Medicine, Yale University, 100 College St, New Haven, CT, 06511, USA. xianjun.dong@yale.edu.
  • Bai Y; Department of Neurology, Yale School of Medicine, Yale University, 100 College St, New Haven, CT, 06511, USA. xianjun.dong@yale.edu.
Oncogene ; 43(41): 3021-3036, 2024 Oct.
Article in En | MEDLINE | ID: mdl-39209966
ABSTRACT
Extrachromosomal circular DNAs (eccDNAs) are a unique class of chromosome-originating circular DNA molecules, which are closely linked to oncogene amplification. Due to recent technological advances, particularly in high-throughput sequencing technology, bioinformatics methods based on sequencing data have become primary approaches for eccDNA identification and functional analysis. Currently, eccDNA-relevant databases incorporate previously identified eccDNA and provide thorough functional annotations and predictions, thereby serving as a valuable resource for eccDNA research. In this review, we collected around 20 available eccDNA-associated bioinformatics tools, including identification tools and annotation databases, and summarized their properties and capabilities. We evaluated some of the eccDNA detection methods in simulated data to offer recommendations for future eccDNA detection. We also discussed the current limitations and prospects of bioinformatics methodologies in eccDNA research.
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: DNA, Circular / Computational Biology Limits: Humans Language: En Journal: Oncogene Journal subject: BIOLOGIA MOLECULAR / NEOPLASIAS Year: 2024 Document type: Article Country of publication: United kingdom

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: DNA, Circular / Computational Biology Limits: Humans Language: En Journal: Oncogene Journal subject: BIOLOGIA MOLECULAR / NEOPLASIAS Year: 2024 Document type: Article Country of publication: United kingdom