6mA-Finder: a novel online tool for predicting DNA N6-methyladenine sites in genomes

被引:32
|
作者
Xu, Haodong [1 ]
Hu, Ruifeng [1 ]
Jia, Peilin [1 ]
Zhao, Zhongming [1 ,2 ,3 ]
机构
[1] UTHlth Grad Sch Biomed Sci, Sch Biomed Informat, Ctr Precis Hlth, Houston, TX 77030 USA
[2] UTHlth Grad Sch Biomed Sci, MD Anderson Canc Ctr, Houston, TX 77030 USA
[3] Vanderbilt Univ, Med Ctr, Dept Biomed Informat, Nashville, TN 37203 USA
关键词
METHYLATION; N-6-ADENINE;
D O I
10.1093/bioinformatics/btaa113
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Motivation: DNA N6-methyladenine (6mA) has recently been found as an essential epigenetic modification, playing its roles in a variety of cellular processes. The abnormal status of DNA 6mA modification has been reported in cancer and other disease. The annotation of 6mA marks in genome is the first crucial step to explore the underlying molecular mechanisms including its regulatory roles. Results: We present a novel online DNA 6mA site tool, 6mA-Finder, by incorporating seven sequence-derived information and three physicochemical-based features through recursive feature elimination strategy. Our multiple cross-validations indicate the promising accuracy and robustness of our model. 6mA-Finder outperforms its peer tools in general and species-specific 6mA site prediction, suggesting it can provide a useful resource for further experimental investigation of DNA 6mA modification.
引用
收藏
页码:3257 / 3259
页数:3
相关论文
共 50 条
  • [1] SpineNet-6mA: A Novel Deep Learning Tool for Predicting DNA N6-Methyladenine Sites in Genomes
    Abbas, Zeeshan
    Tayara, Hilal
    Chong, Kil To
    IEEE ACCESS, 2020, 8 : 201450 - 201457
  • [2] Plant6mA: A predictor for predicting N6-methyladenine sites with lightweight structure in plant genomes
    Shi, Hua
    Li, Shuang
    Su, Xi
    METHODS, 2022, 204 : 126 - 131
  • [3] A Deep Learning Model for Predicting DNA N6-Methyladenine (6mA) Sites in Eukaryotes
    Roland, Lokuthota Hewage
    Wannige, Champi Thusangi
    IEEE ACCESS, 2020, 8 : 175535 - 175545
  • [4] A review of methods for predicting DNA N6-methyladenine sites
    Han, Ke
    Wang, Jianchun
    Wang, Yu
    Zhang, Lei
    Yu, Mengyao
    Xie, Fang
    Zheng, Dequan
    Xu, Yaoqun
    Ding, Yijie
    Wan, Jie
    BRIEFINGS IN BIOINFORMATICS, 2023, 24 (01)
  • [5] SNNRice6mA: A Deep Learning Method for Predicting DNA N6-Methyladenine Sites in Rice Genome
    Yu, Haitao
    Dai, Zhiming
    FRONTIERS IN GENETICS, 2019, 10
  • [6] SoftVoting6mA: An improved ensemble-based method for predicting DNA N6-methyladenine sites in cross-species genomes
    Yin Z.
    Lyu J.
    Zhang G.
    Huang X.
    Ma Q.
    Jiang J.
    Mathematical Biosciences and Engineering, 2024, 21 (03) : 3798 - 3815
  • [7] iDNA6mA-Rice: A Computational Tool for Detecting N6-Methyladenine Sites in Rice
    Lv, Hao
    Dao, Fu-Ying
    Guan, Zheng-Xing
    Zhang, Dan
    Tan, Jiu-Xin
    Zhang, Yong
    Chen, Wei
    Lin, Hao
    FRONTIERS IN GENETICS, 2019, 10
  • [8] i6mA-word2vec: A Newly Model Which Used Distributed Features for Predicting DNA N6-Methyladenine Sites in Genomes
    Fu, Wenzhen
    Zhong, Yixin
    Chen, Baitong
    Cao, Yi
    Chen, Jiazi
    Cong, Hanhan
    INTELLIGENT COMPUTING THEORIES AND APPLICATION, ICIC 2022, PT II, 2022, 13394 : 670 - 679
  • [9] i6mA-CNN: A Web-based System to Identify DNA N6-Methyladenine Sites in Mouse Genomes
    Nguyen-Vo, Thanh-Hoang
    Rahardja, Susanto
    Nguyen, Binh P.
    2024 IEEE INTERNATIONAL SYMPOSIUM ON CIRCUITS AND SYSTEMS, ISCAS 2024, 2024,
  • [10] 6mA-Pred: identifying DNA N6-methyladenine sites based on deep learning
    Huang, Qianfei
    Zhou, Wenyang
    Guo, Fei
    Xu, Lei
    Zhang, Lichao
    PEERJ, 2021, 9