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Global analysis of N6-methyladenosine functions and its disease association using deep learning and network-based methods
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1002/hep.29683openalex-snapshot
RNA N6‐methyladenosine methyltransferase‐like 3 promotes liver cancer progression through YTHDF2‐dependent posttranscriptional silencing of SOCS2
inferredcites →https://doi.org/10.1016/0197-2456(81)90001-5openalex-snapshot
Introduction to sample size determination and power analysis for clinical trials
inferredcites →https://doi.org/10.1016/j.ab.2015.08.021openalex-snapshot
iRNA-Methyl: Identifying N6-methyladenosine sites using pseudo nucleotide composition
inferredcites →https://doi.org/10.1016/j.ab.2015.12.017openalex-snapshot
pRNAm-PC: Predicting N6-methyladenosine sites in RNA sequences via physical–chemical properties
inferredcites →https://doi.org/10.1016/j.ccell.2016.11.017openalex-snapshot
FTO Plays an Oncogenic Role in Acute Myeloid Leukemia as a N 6 -Methyladenosine RNA Demethylase
inferredcites →https://doi.org/10.1016/j.ccell.2017.02.013openalex-snapshot
m 6 A Demethylase ALKBH5 Maintains Tumorigenicity of Glioblastoma Stem-like Cells by Sustaining FOXM1 Expression and Cell Proliferation Program
inferredcites →https://doi.org/10.1016/j.cell.2007.04.019openalex-snapshot
Hypoxia-Inducible Factors, Stem Cells, and Cancer
inferredcites →https://doi.org/10.1016/j.cell.2012.05.003openalex-snapshot
Comprehensive Analysis of mRNA Methylation Reveals Enrichment in 3′ UTRs and near Stop Codons
inferredcites →https://doi.org/10.1016/j.cell.2013.10.026openalex-snapshot
RNA-Methylation-Dependent RNA Processing Controls the Speed of the Circadian Clock
inferredcites →https://doi.org/10.1016/j.cell.2015.05.014openalex-snapshot
N6-methyladenosine Modulates Messenger RNA Translation Efficiency
inferredcites →https://doi.org/10.1016/j.cell.2017.03.031openalex-snapshot
Transcription Impacts the Efficiency of mRNA Translation via Co-transcriptional N6-adenosine Methylation
inferredcites →https://doi.org/10.1016/j.chom.2016.04.002openalex-snapshot
Posttranscriptional m6A Editing of HIV-1 mRNAs Enhances Viral Gene Expression
inferredcites →https://doi.org/10.1016/j.chom.2016.10.002openalex-snapshot
Dynamics of Human and Viral RNA Methylation during Zika Virus Infection
inferredcites →https://doi.org/10.1016/j.molcel.2012.10.015openalex-snapshot
ALKBH5 Is a Mammalian RNA Demethylase that Impacts RNA Metabolism and Mouse Fertility
inferredcites →https://doi.org/10.1016/j.molcel.2016.03.021openalex-snapshot
The m 6 A Methyltransferase METTL3 Promotes Translation in Human Cancer Cells
inferredcites →https://doi.org/10.1016/j.neucom.2018.04.082openalex-snapshot
Integration of deep feature representations and handcrafted features to improve the prediction of N6-methyladenosine sites
inferredcites →https://doi.org/10.1016/j.ymeth.2014.06.008openalex-snapshot
A protocol for RNA methylation differential analysis with MeRIP-Seq data and exomePeak R/Bioconductor package
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Linking Colorectal Cancer to Wnt Signaling
inferredcites →https://doi.org/10.1038/cr.2014.151openalex-snapshot
FTO-dependent demethylation of N6-methyladenosine regulates mRNA splicing and is required for adipogenesis
inferredcites →https://doi.org/10.1038/cr.2014.3openalex-snapshot
Mammalian WTAP is a regulatory subunit of the RNA N6-methyladenosine methyltransferase
inferredcites →https://doi.org/10.1038/leu.2014.16openalex-snapshot
WTAP is a novel oncogenic protein in acute myeloid leukemia
inferredcites →https://doi.org/10.1038/nature03319openalex-snapshot
Wnt signalling in stem cells and cancer
inferredcites →https://doi.org/10.1038/nature11112openalex-snapshot
Topology of the human and mouse m6A RNA methylomes revealed by m6A-seq
inferredcites →https://doi.org/10.1038/nature15377openalex-snapshot
Dynamic m6A mRNA methylation directs translational control of heat shock response
inferredcites →https://doi.org/10.1038/nature24678openalex-snapshot
Promoter-bound METTL3 maintains myeloid leukaemia by m6A-dependent translation control
inferredcites →https://doi.org/10.1038/ncb2902openalex-snapshot
N6-methyladenosine modification destabilizes developmental regulators in embryonic stem cells
inferredcites →https://doi.org/10.1038/ng.3168openalex-snapshot
Pan-cancer network analysis identifies combinations of rare somatic mutations across pathways and protein complexes
inferredcites →https://doi.org/10.1038/nm.4416openalex-snapshot
The N6-methyladenosine (m6A)-forming enzyme METTL3 controls myeloid differentiation of normal hematopoietic and leukemia cells
inferredcites →https://doi.org/10.1038/nmeth.1597openalex-snapshot
Next-generation sequencing to generate interactome datasets
inferredcites →https://doi.org/10.1038/nmeth.3453openalex-snapshot
Single-nucleotide-resolution mapping of m6A and m6Am throughout the transcriptome
inferredcites →https://doi.org/10.1038/nprot.2012.016openalex-snapshot
Differential gene and transcript expression analysis of RNA-seq experiments with TopHat and Cufflinks
inferredcites →https://doi.org/10.1038/s41564-017-0056-8openalex-snapshot
Viral and cellular N6-methyladenosine and N6,2′-O-dimethyladenosine epitranscriptomes in the KSHV life cycle
inferredcites →https://doi.org/10.1038/srep40242openalex-snapshot
Detecting N6-methyladenosine sites from RNA transcriptomes using ensemble Support Vector Machines
inferredcites →https://doi.org/10.1038/srep46757openalex-snapshot
Identifying N6-methyladenosine sites using multi-interval nucleotide pair position specificity and support vector machine
inferredcites →https://doi.org/10.1039/c6mb00536eopenalex-snapshot
AthMethPre: a web server for the prediction and query of mRNA m6A sites in Arabidopsis thaliana
inferredcites →https://doi.org/10.1073/pnas.1602883113openalex-snapshot
Hypoxia induces the breast cancer stem cell phenotype by HIF-dependent and ALKBH5-mediated m 6 A-demethylation of NANOG mRNA
inferredcites →https://doi.org/10.1074/jbc.m706082200openalex-snapshot
Post-transcriptional Regulation of Neuro-oncological Ventral Antigen 1 by the Neuronal RNA-binding Proteins ELAV
inferredcites →https://doi.org/10.1080/07391102.2016.1157761openalex-snapshot
MethyRNA: a web server for identification of N6-methyladenosine sites
inferredcites →https://doi.org/10.1093/bioinformatics/btq108openalex-snapshot
Genome-wide inferring gene–phenotype relationship by walking on the heterogeneous network
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Gene expression inference with deep learning
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A novel algorithm for calling mRNA m 6 A peaks by modeling biological variances in MeRIP-seq data
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DisGeNET: a discovery platform for the dynamical exploration of human diseases and their genes
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inferredcites →https://doi.org/10.1093/gigascience/giy035openalex-snapshot
m6ASNP: a tool for annotating genetic variants by m6A function
inferredcites →https://doi.org/10.1093/nar/30.1.52openalex-snapshot
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inferredcites →https://doi.org/10.1093/nar/gki033openalex-snapshot
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inferredcites →https://doi.org/10.1093/nar/gkr972openalex-snapshot
Disease Ontology: a backbone for disease semantic integration
inferredcites →https://doi.org/10.1093/nar/gku1204openalex-snapshot
The BioGRID interaction database: 2015 update
inferredcites →https://doi.org/10.1093/nar/gkw104openalex-snapshot
SRAMP: prediction of mammalian N 6 -methyladenosine (m 6 A) sites based on sequence-derived features
inferredcites →https://doi.org/10.1093/nar/gkx1080openalex-snapshot
MeT-DB V2.0: elucidating context-specific functions of N6-methyl-adenosine methyltranscriptome
inferredcites →https://doi.org/10.1101/gad.269415.115openalex-snapshot
A majority of m6A residues are in the last exons, allowing the potential for 3′ UTR regulation
inferredcites →https://doi.org/10.1109/5.726791openalex-snapshot
Gradient-based learning applied to document recognition
inferredcites →https://doi.org/10.1109/tcbb.2015.2403355openalex-snapshot
MeTDiff: A Novel Differential RNA Methylation Analysis for MeRIP-Seq Data
inferredcites →https://doi.org/10.1109/tcbb.8857openalex-snapshot
IEEE/ACM Transactions on Computational Biology and Bioinformatics
inferredcites →https://doi.org/10.1111/j.2517-6161.1953.tb00135.xopenalex-snapshot
New Light on the Correlation Coefficient and its Transforms
inferredcites →https://doi.org/10.1155/2016/8367534openalex-snapshot
Guitar: An R/Bioconductor Package for Gene Annotation Guided Transcriptomic Analysis of RNA-Related Genomic Features
inferredcites →https://doi.org/10.1158/1538-7445.am2014-5324openalex-snapshot
Abstract 5324: Pan-cancer identification of mutated pathways and protein complexes
inferredcites →https://doi.org/10.1158/2159-8290.cd-16-1292openalex-snapshot
The Epitranscriptome of Noncoding RNAs in Cancer
inferredcites →https://doi.org/10.1186/1471-2105-9-405openalex-snapshot
iRefIndex: A consolidated protein interaction database with provenance
inferredcites →https://doi.org/10.1186/1471-2350-12-52openalex-snapshot
The role of the fat mass and obesity associated gene (FTO) in breast cancer risk
inferredcites →https://doi.org/10.1186/1752-0509-6-92openalex-snapshot
HINT: High-quality protein interactomes and their applications in understanding human disease
inferredcites →https://doi.org/10.1186/gb-2003-4-5-p3openalex-snapshot
DAVID: Database for Annotation, Visualization, and Integrated Discovery
inferredcites →https://doi.org/10.1186/gb-2003-4-9-r60openalex-snapshot
DAVID: Database for Annotation, Visualization, and Integrated Discovery
inferredcites →https://doi.org/10.1186/s13073-016-0395-8openalex-snapshot
Emerging links between m6A and misregulated mRNA methylation in cancer
inferredcites →https://doi.org/10.1210/jc.2018-00619openalex-snapshot
Glucose Is Involved in the Dynamic Regulation of m6A in Patients With Type 2 Diabetes
inferredcites →https://doi.org/10.1371/journal.pcbi.1002886openalex-snapshot
Interpretation of Genomic Variants Using a Unified Biological Network Approach
inferredcites →https://doi.org/10.1371/journal.pcbi.1005287openalex-snapshot
m6A-Driver: Identifying Context-Specific mRNA m6A Methylation-Driven Gene Interaction Networks
inferredcites →https://doi.org/10.1371/journal.pone.0058350openalex-snapshot
Evaluating Genome-Wide Association Study-Identified Breast Cancer Risk Variants in African-American Women
inferredcites →https://doi.org/10.1371/journal.pone.0162707openalex-snapshot
RNAMethPre: A Web Server for the Prediction and Query of mRNA m6A Sites
inferredcites →https://doi.org/10.1515/cclm-2013-0168openalex-snapshot
ABO blood group: old dogma, new perspectives
inferredcites →https://doi.org/10.18632/oncotarget.21726openalex-snapshot
The M6A methyltransferase METTL3: acting as a tumor suppressor in renal cell carcinoma
inferredcites →https://doi.org/10.18632/oncotarget.22041openalex-snapshot
Reduced m6A mRNA methylation is correlated with the progression of human cervical cancer
inferredcites →https://doi.org/10.2174/1568009023334088openalex-snapshot
WT1 as a Novel Target Antigen for Cancer Immunotherapy
inferredcites →https://doi.org/10.48550/arxiv.1212.5701openalex-snapshot
ADADELTA: An Adaptive Learning Rate Method
inferredcites →https://doi.org/10.48550/arxiv.cond-mat/0312028openalex-snapshot
On the uniform generation of random graphs with prescribed degree sequences
inferredcites →https://doi.org/10.7554/elife.15528openalex-snapshot
N6-methyladenosine of HIV-1 RNA regulates viral infection and HIV-1 Gag protein expression
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1007/s11103-019-00930-xopenalex-snapshot
HLMethy: a machine learning-based model to identify the hidden labels of m6A candidates
inferred← citeshttps://doi.org/10.1016/j.ab.2021.114120openalex-snapshot
ES-ARCNN: Predicting enhancer strength by using data augmentation and residual convolutional neural network
inferred← citeshttps://doi.org/10.1016/j.bpc.2025.107417openalex-snapshot
Systematic molecular profiling of non-native N6-substitution effects on m6A binding to the YTH domains of human RNA m6A readers in diabetes
inferred← citeshttps://doi.org/10.1016/j.csbj.2020.06.010openalex-snapshot
Bioinformatics approaches for deciphering the epitranscriptome: Recent progress and emerging topics
inferred← citeshttps://doi.org/10.1016/j.csbj.2021.05.030openalex-snapshot
Recent advances in functional annotation and prediction of the epitranscriptome
inferred← citeshttps://doi.org/10.1016/j.neucom.2019.08.084openalex-snapshot
LPI-BLS: Predicting lncRNA–protein interactions with a broad learning system-based stacked ensemble classifier
inferred← citeshttps://doi.org/10.1016/j.omto.2020.04.011openalex-snapshot
The m6A-Related mRNA Signature Predicts the Prognosis of Pancreatic Cancer Patients
inferred← citeshttps://doi.org/10.1016/j.ymeth.2022.03.008openalex-snapshot
m6Aexpress-Reader: Prediction of m6A regulated expression genes by integrating m6A sites and reader binding information in specific- context
inferred← citeshttps://doi.org/10.1016/j.ymeth.2022.04.002openalex-snapshot
m6Acancer-Net: Identification of m6A-mediated cancer driver genes from gene-site heterogeneous network
inferred← citeshttps://doi.org/10.1016/j.ymeth.2022.07.011openalex-snapshot
Advances in detecting N6-methyladenosine modification in circRNAs
inferred← citeshttps://doi.org/10.1016/j.ymeth.2024.04.011openalex-snapshot
m6Aexpress-enet: Predicting the regulatory expression m6A sites by an enet-regularization negative binomial regression model
inferred← citeshttps://doi.org/10.1021/acsomega.5c02422openalex-snapshot
DeepAIPs-SFLA: Deep Convolutional Model for Prediction of Anti-Inflammatory Peptides Using Binary Pattern Decomposition of Novel Multiview Descriptors with an SFLA Approach
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The ameliorative effect of CangFu Daotan Decoction on polycystic ovary syndrome of rodent model is associated with m6A methylation and Wnt/β-catenin pathway
inferred← citeshttps://doi.org/10.1093/bib/bbac295openalex-snapshot
m6 Aexpress-BHM: predicting m6A regulation of gene expression in multiple-groups context by a Bayesian hierarchical mixture model
inferred← citeshttps://doi.org/10.1093/bib/bbad163openalex-snapshot
Concepts and methods for transcriptome-wide prediction of chemical messenger RNA modifications with machine learning
inferred← citeshttps://doi.org/10.1093/bioinformatics/btaa178openalex-snapshot
m7GHub: deciphering the location, regulation and pathogenesis of internal mRNA N7-methylguanosine (m7G) sites in human
inferred← citeshttps://doi.org/10.1093/bioinformatics/btab362openalex-snapshot
Funm6AViewer: a web server and R package for functional analysis of context-specific m6A RNA methylation
inferred← citeshttps://doi.org/10.1093/bioinformatics/btz316openalex-snapshot
FunDMDeep-m6A: identification and prioritization of functional differential m6A methylation genes
inferred← citeshttps://doi.org/10.1093/nar/gkab714openalex-snapshot
m6A-express: uncovering complex and condition-specific m6A regulation of gene expression
inferred← citeshttps://doi.org/10.1093/nargab/lqaa007openalex-snapshot
Deep analysis of RNA N6-adenosine methylation (m6A) patterns in human cells
inferred← citeshttps://doi.org/10.1155/2021/5573628openalex-snapshot
Screening and Identifying m6A Regulators as an Independent Prognostic Biomarker in Pancreatic Cancer Based on The Cancer Genome Atlas Database
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Research on Collaborative Optimization Model of Tourism Resources and Highway Network Based on IoT Network and Deep Learning
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Predict Epitranscriptome Targets and Regulatory Functions of N 6 -Methyladenosine (m 6 A) Writers and Erasers
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Prediction of RNA Methylation Status From Gene Expression Data Using Classification and Regression Methods
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PSI-MOUSE: Predicting Mouse Pseudouridine Sites From Sequence and Genome-Derived Features
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ELABELA targets the METTL3/PI3K/AKT axis to enhance trophoblast invasion in early-onset preeclampsia
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RETRACTED ARTICLE: m6A demethylase ALKBH5 inhibits pancreatic cancer tumorigenesis by decreasing WIF-1 RNA methylation and mediating Wnt signaling
inferred← citeshttps://doi.org/10.21203/rs.3.rs-96939/v1openalex-snapshot
Screening and Identifying m6A Regulators in Pancreatic Cancer Based on The Cancer Genome Atlas Database
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WITMSG: Large-scale Prediction of Human Intronic m6A RNA Methylation Sites from Sequence and Genomic Features
inferred← citeshttps://doi.org/10.3389/fcell.2020.00741openalex-snapshot
m6A Reader: Epitranscriptome Target Prediction and Functional Characterization of N6-Methyladenosine (m6A) Readers
inferred← citeshttps://doi.org/10.3389/fcell.2023.1136096openalex-snapshot
Comprehensive analysis of differences in N6-methyladenosine RNA methylomes in Helicobacter pylori infection
inferred← citeshttps://doi.org/10.3389/fgene.2019.00266openalex-snapshot
DRUM: Inference of Disease-Associated m6A RNA Methylation Sites From a Multi-Layer Heterogeneous Network
inferred← citeshttps://doi.org/10.3389/fgene.2020.00398openalex-snapshot
How Do You Identify m6 A Methylation in Transcriptomes at High Resolution? A Comparison of Recent Datasets
inferred← citeshttps://doi.org/10.3389/fgene.2020.00545openalex-snapshot
LITHOPHONE: Improving lncRNA Methylation Site Prediction Using an Ensemble Predictor
inferred← citeshttps://doi.org/10.3389/fgene.2022.1030275openalex-snapshot
A novel prognostic signature based on N7-methylguanosine-related long non-coding RNAs in breast cancer
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Effects of m6A methylation of MAT2A mRNA regulated by METTL16 on learning and memory, hippocampal synaptic plasticity and Aβ1–42 in 5 × FAD mice
inferred← citeshttps://doi.org/10.3390/ijms22126254openalex-snapshot
Transcriptome Profiling of m6A mRNA Modification in Bovine Mammary Epithelial Cells Treated with Escherichia coli
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Reduction of Methyltransferase-like 3-Mediated RNA N6-Methyladenosine Exacerbates the Development of Psoriasis Vulgaris in Imiquimod-Induced Psoriasis-like Mouse Model
inferred← citeshttps://doi.org/10.3892/etm.2020.9267openalex-snapshot
Silencing of methyltransferase-like 3 inhibits oesophageal squamous cell carcinoma.
inferred← citeshttps://doi.org/10.7554/elife.100601openalex-snapshot
Phase transition of WTAP regulates m6A modification of interferon-stimulated genes
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Phase transition of WTAP regulates m6A modification of interferon-stimulated genes
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