DNA sequences performs as natural language processing by exploiting deep learning algorithm for the identification of N4-methylcytosine
Published 2021 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
DNA sequences performs as natural language processing by exploiting deep learning algorithm for the identification of N4-methylcytosine
Authors
Keywords
-
Journal
Scientific Reports
Volume 11, Issue 1, Pages -
Publisher
Springer Science and Business Media LLC
Online
2021-01-08
DOI
10.1038/s41598-020-80430-x
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- A Deep Neural Network for Identifying DNA N4-Methylcytosine Sites
- (2020) Feng Zeng et al. Frontiers in Genetics
- SEEK: A Framework of Superpixel Learning with CNN Features for Unsupervised Segmentation
- (2020) Talha Ilyas et al. Electronics
- iMethyl-Deep: N6 Methyladenosine Identification of Yeast Genome with Automatic Feature Extraction Technique by Using Deep Learning Algorithm
- (2020) Omid Mahmoudi et al. Genes
- DNA6mA-MINT: DNA-6mA Modification Identification Neural Tool
- (2020) Mobeen Ur Rehman et al. Genes
- DNC4mC-Deep: Identification and Analysis of DNA N4-Methylcytosine Sites Based on Different Encoding Schemes By Using Deep Learning
- (2020) Abdul Wahab et al. Cells
- i6mA-DNC: Prediction of DNA N6-Methyladenosine sites in rice genome based on dinucleotide representation using deep learning
- (2020) Sehi Park et al. CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS
- CED-Net: Crops and Weeds Segmentation for Smart Farming Using a Small Cascaded Encoder-Decoder Architecture
- (2020) Abbas Khan et al. Electronics
- Iterative feature representations improve N4-methylcytosine site prediction
- (2019) Leyi Wei et al. BIOINFORMATICS
- iSS-CNN: Identifying splicing sites using convolution neural network
- (2019) Hilal Tayara et al. CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS
- iPseU-CNN: Identifying RNA Pseudouridine Sites Using Convolutional Neural Networks
- (2019) Muhammad Tahir et al. Molecular Therapy-Nucleic Acids
- Meta-4mCpred: A Sequence-Based Meta-Predictor for Accurate DNA 4mC Site Prediction Using Effective Feature Representation
- (2019) Balachandran Manavalan et al. Molecular Therapy-Nucleic Acids
- iN6-Methyl (5-step): Identifying RNA N6-methyladenosine sites using deep learning mode via Chou's 5-step rules and Chou's general PseKNC
- (2019) Iman Nazari et al. CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS
- Improving the Quantification of DNA Sequences Using Evolutionary Information Based on Deep Learning
- (2019) Hilal Tayara et al. Cells
- DNA N 6 -Adenine Methylation in Arabidopsis thaliana
- (2018) Zhe Liang et al. DEVELOPMENTAL CELL
- Recent Trends in Deep Learning Based Natural Language Processing [Review Article]
- (2018) Tom Young et al. IEEE Computational Intelligence Magazine
- M6APred-EL: A sequence-based predictor for identifying N6-methyladenosine sites using ensemble learning
- (2018) Leyi Wei et al. Molecular Therapy-Nucleic Acids
- 4mCPred: Machine Learning Methods for DNA N4-methylcytosine sites Prediction
- (2018) Wenying He et al. BIOINFORMATICS
- Identifying antimicrobial peptides using word embedding with deep recurrent neural networks
- (2018) Md-Nafiz Hamid et al. BIOINFORMATICS
- A primer on deep learning in genomics
- (2018) James Zou et al. NATURE GENETICS
- Large-scale in-silico statistical mutagenesis analysis sheds light on the deleteriousness landscape of the human proteome
- (2018) Daniele Raimondi et al. Scientific Reports
- iRNA-PseKNC(2methyl): Identify RNA 2'-O-methylation sites by convolution neural network and Chou's pseudo components
- (2018) Muhammad Tahir et al. JOURNAL OF THEORETICAL BIOLOGY
- MethSMRT: an integrative database for DNA N6-methyladenine and N4-methylcytosine generated by single-molecular real-time sequencing
- (2016) Pohao Ye et al. NUCLEIC ACIDS RESEARCH
- Epigenetic regulatory functions of DNA modifications: 5-methylcytosine and beyond
- (2015) Achim Breiling et al. Epigenetics & Chromatin
- DNA methylation and epigenomics: new technologies and emerging concepts
- (2015) Aniruddha Chatterjee et al. GENOME BIOLOGY
- Exploring genome wide bisulfite sequencing for DNA methylation analysis in livestock: a technical assessment
- (2014) Rachael Doherty et al. Frontiers in Genetics
- Representation Learning: A Review and New Perspectives
- (2013) Y. Bengio et al. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
- CD-HIT: accelerated for clustering the next-generation sequencing data
- (2012) Limin Fu et al. BIOINFORMATICS
- XanthomonasAvrBs3 Family-Type III Effectors: Discovery and Function
- (2010) Jens Boch et al. Annual Review of Phytopathology
- Direct detection of DNA methylation during single-molecule, real-time sequencing
- (2010) Benjamin A Flusberg et al. NATURE METHODS
- Establishing, maintaining and modifying DNA methylation patterns in plants and animals
- (2010) Julie A. Law et al. NATURE REVIEWS GENETICS
- DNA methylation landscapes: provocative insights from epigenomics
- (2008) Miho M. Suzuki et al. NATURE REVIEWS GENETICS
Find Funding. Review Successful Grants.
Explore over 25,000 new funding opportunities and over 6,000,000 successful grants.
ExploreBecome a Peeref-certified reviewer
The Peeref Institute provides free reviewer training that teaches the core competencies of the academic peer review process.
Get Started