Gene2vec: gene subsequence embedding for prediction of mammalian N 6-methyladenosine sites from mRNA

scientific article published on 13 November 2018

Gene2vec: gene subsequence embedding for prediction of mammalian N 6-methyladenosine sites from mRNA is …
instance of (P31):
scholarly articleQ13442814

External links are
P356DOI10.1261/RNA.069112.118
P932PMC publication ID6348985
P698PubMed publication ID30425123

P50authorQuan ZouQ37831673
P2093author name stringBin Liu
Pengwei Xing
Leyi Wei
P2860cites workTopology of the human and mouse m6A RNA methylomes revealed by m6A-seqQ24320240
Comprehensive analysis of mRNA methylation reveals enrichment in 3' UTRs and near stop codonsQ24598126
Deep learning for computational biologyQ26740441
N6-Methyladenosine in Flaviviridae Viral RNA Genomes Regulates InfectionQ27485442
Dynamics of Human and Viral RNA Methylation during Zika Virus InfectionQ27486503
Quantifying similarity between motifsQ27499384
High-resolution mapping reveals a conserved, widespread, dynamic mRNA methylation program in yeast meiosisQ27930684
A majority of m6A residues are in the last exons, allowing the potential for 3' UTR regulationQ28267771
Stem cells. m6A mRNA methylation facilitates resolution of naïve pluripotency toward differentiationQ28511267
RNA-methylation-dependent RNA processing controls the speed of the circadian clockQ28591141
DeepCpG: accurate prediction of single-cell DNA methylation states using deep learningQ30358676
nDNA-Prot: identification of DNA-binding proteins based on unbalanced classification.Q30366530
A compendium of RNA-binding motifs for decoding gene regulation.Q34357005
Predicting the sequence specificities of DNA- and RNA-binding proteins by deep learningQ34487019
Dynamics of the human and viral m(6)A RNA methylomes during HIV-1 infection of T cells.Q34538813
Unique features of the m6A methylome in Arabidopsis thaliana.Q34589890
Single-nucleotide-resolution mapping of m6A and m6Am throughout the transcriptomeQ35804751
Pse-in-One: a web server for generating various modes of pseudo components of DNA, RNA, and protein sequencesQ35810290
RNA N6-methyladenosine methylation in post-transcriptional gene expression regulationQ35879032
Identification and analysis of the N(6)-methyladenosine in the Saccharomyces cerevisiae transcriptomeQ36032178
RNAMethPre: A Web Server for the Prediction and Query of mRNA m6A SitesQ36159513
Transcriptome-wide high-throughput deep m(6)A-seq reveals unique differential m(6)A methylation patterns between three organs in Arabidopsis thaliana.Q36466905
SRAMP: prediction of mammalian N6-methyladenosine (m6A) sites based on sequence-derived featuresQ36958992
Transcriptome-wide N⁶-methyladenosine profiling of rice callus and leaf reveals the presence of tissue-specific competitors involved in selective mRNA modificationQ37501658
m6A Demethylase ALKBH5 Maintains Tumorigenicity of Glioblastoma Stem-like Cells by Sustaining FOXM1 Expression and Cell Proliferation ProgramQ38710467
Identify and analysis crotonylation sites in histone by using support vector machines.Q38914180
PhosPred-RF: A Novel Sequence-Based Predictor for Phosphorylation Sites Using Sequential Information Only.Q38976242
m(6)A RNA methylation is regulated by microRNAs and promotes reprogramming to pluripotencyQ39038754
Identifying N 6-methyladenosine sites in the Arabidopsis thaliana transcriptome.Q39426618
iRSpot-EL: identify recombination spots with an ensemble learning approachQ39484248
Detecting N6-methyladenosine sites from RNA transcriptomes using ensemble Support Vector MachinesQ41353622
Identifying N6-methyladenosine sites using multi-interval nucleotide pair position specificity and support vector machine.Q42290571
iRNA-PseU: Identifying RNA pseudouridine sitesQ42319212
Protein remote homology detection based on bidirectional long short-term memoryQ42374176
Chromatin accessibility prediction via a hybrid deep convolutional neural networkQ42695563
DeepLoc: prediction of protein subcellular localization using deep learningQ42696047
Sequence2Vec: A novel embedding approach for modeling transcription factor binding affinity landscapeQ42696829
Chromatin accessibility prediction via convolutional long short-term memory networks with k-mer embeddingQ42697270
ProLanGO: Protein Function Prediction Using Neural Machine Translation Based on a Recurrent Neural Network.Q45944894
Fast prediction of protein methylation sites using a sequence-based feature selection technique.Q45948462
MeT-DB V2.0: elucidating context-specific functions of N6-methyl-adenosine methyltranscriptome.Q46008109
RMBase v2.0: deciphering the map of RNA modifications from epitranscriptome sequencing dataQ46282727
iDNA4mC: identifying DNA N4-methylcytosine sites based on nucleotide chemical properties.Q46298862
Deep learning of the splicing (epi)genetic code reveals a novel candidate mechanism linking histone modifications to ESC fate decisionQ47112458
Ensembl 2018.Q47151007
R-2HG Exhibits Anti-tumor Activity by Targeting FTO/m6A/MYC/CEBPA Signaling.Q47284426
RFAthM6A: a new tool for predicting m6A sites in Arabidopsis thaliana.Q47562249
m6A RNA Methylation Regulates the Self-Renewal and Tumorigenesis of Glioblastoma Stem Cells.Q47583443
DephosSitePred: A High Accuracy Predictor for Protein Dephosphorylation SitesQ48027898
O-GlcNAcPRED-II: an integrated classification algorithm for identifying O-GlcNAcylation sites based on fuzzy undersampling and a K-means PCA oversampling techniqueQ50114032
iRNA-Methyl: Identifying N(6)-methyladenosine sites using pseudo nucleotide composition.Q50567651
FTO Plays an Oncogenic Role in Acute Myeloid Leukemia as a N6-Methyladenosine RNA Demethylase.Q51236778
N6-methyladenosine modification and the YTHDF2 reader protein play cell type specific roles in lytic viral gene expression during Kaposi's sarcoma-associated herpesvirus infection.Q54235221
iRNA-3typeA: Identifying Three Types of Modification at RNA's Adenosine Sites.Q55162021
Prediction of enhancer-promoter interactions via natural language processing.Q55221664
70ProPred: a predictor for discovering sigma70 promoters based on combining multiple features.Q55241645
METTL3-mediated m6A modification is required for cerebellar development.Q55513357
Survey of Machine Learning Techniques in Drug DiscoveryQ57168570
IDP⁻CRF: Intrinsically Disordered Protein/Region Identification Based on Conditional Random FieldsQ58717213
Alternative splicing links histone modifications to stem cell fate decisionQ58740511
MethyRNA: a web server for identification of N6-methyladenosine sitesQ87361552
Applications of Single-Cell Sequencing for MultiomicsQ88047814
ProtDet-CCH: Protein Remote Homology Detection by Combining Long Short-Term Memory and Ranking MethodsQ89557141
Exploring sequence-based features for the improved prediction of DNA N4-methylcytosine sites in multiple speciesQ91618176
Deep learning in omics: a survey and guidelineQ91845591
P433issue2
P304page(s)205-218
P577publication date2018-11-13
P1433published inRNAQ7277164
P1476titleGene2vec: gene subsequence embedding for prediction of mammalian N 6-methyladenosine sites from mRNA
P478volume25

Reverse relations

cites work (P2860)
Q90267375A Random Forest Sub-Golgi Protein Classifier Optimized via Dipeptide and Amino Acid Composition Features
Q64881052ACP-DL: A Deep Learning Long Short-Term Memory Model to Predict Anticancer Peptides Using High-Efficiency Feature Representation.
Q90206421ATC-NLSP: Prediction of the Classes of Anatomical Therapeutic Chemicals Using a Network-Based Label Space Partition Method
Q92237046Accurate classification of membrane protein types based on sequence and evolutionary information using deep learning
Q92355759AtbPpred: A Robust Sequence-Based Prediction of Anti-Tubercular Peptides Using Extremely Randomized Trees
Q90029906BioSeq-Analysis2.0: an updated platform for analyzing DNA, RNA and protein sequences at sequence level and residue level based on machine learning approaches
Q97521123Bioinformatics approaches for deciphering the epitranscriptome: Recent progress and emerging topics
Q97646102Comprehensive Analysis of Differentially Expressed lncRNAs in Gastric Cancer
Q94564434Developing a Multi-Layer Deep Learning Based Predictive Model to Identify DNA N4-Methylcytosine Modifications
Q89553735ECFS-DEA: an ensemble classifier-based feature selection for differential expression analysis on expression profiles
Q112691171Evolving deep convolutional neutral network by hybrid sine-cosine and extreme learning machine for real-time COVID19 diagnosis from X-ray images
Q92906098FKRR-MVSF: A Fuzzy Kernel Ridge Regression Model for Identifying DNA-Binding Proteins by Multi-View Sequence Features via Chou's Five-Step Rule
Q64965887Genomic data mining for functional annotation of human long noncoding RNAs.
Q92068735IMPContact: An Interhelical Residue Contact Prediction Method
Q98771680Identifying Cancer-Related lncRNAs Based on a Convolutional Neural Network
Q92177197Is There Any Sequence Feature in the RNA Pseudouridine Modification Prediction Problem?
Q93081066Molecular Computing and Bioinformatics
Q90289535Perspectives of Bioinformatics in Big Data Era
Q91741548Predicting ATP-Binding Cassette Transporters Using the Random Forest Method
Q64245824Predicting Ion Channels Genes and Their Types With Machine Learning Techniques
Q98155076Prediction of N7-methylguanosine sites in human RNA based on optimal sequence features
Q90024987Protein functional annotation of simultaneously improved stability, accuracy and false discovery rate achieved by a sequence-based deep learning
Q90347783RF-PseU: A Random Forest Predictor for RNA Pseudouridine Sites
Q112638897Therapeutic Effect of Electronic Endoscopic Hematoma Removal on Hypertensive Basal Ganglia Cerebral Hemorrhage Based on Smart Medical Technology
Q97519259WITMSG: Large-scale Prediction of Human Intronic m6A RNA Methylation Sites from Sequence and Genomic Features
Q64065592XGBPRH: Prediction of Binding Hot Spots at Protein⁻RNA Interfaces Utilizing Extreme Gradient Boosting
Q90266407iDNA6mA-Rice: A Computational Tool for Detecting N6-Methyladenine Sites in Rice
Q91832728iProEP: A Computational Predictor for Predicting Promoter
Q90457314iRNA-m2G: Identifying N2-methylguanosine Sites Based on Sequence-Derived Information
Q98771745m6A Reader: Epitranscriptome Target Prediction and Functional Characterization of N 6-Methyladenosine (m6A) Readers
Q64250454mACPpred: A Support Vector Machine-Based Meta-Predictor for Identification of Anticancer Peptides

Search more.