| P50 | author | Kunqi Chen | Q90115116 |
| | Hao Xue | Q98177280 |
| P2093 | author name string | Jia Meng | |
| | Zhen Wei | |
| | Jionglong Su | |
| | Yujiao Tang | |
| | Xiangyu Wu | |
| P2860 | cites work | Predicting methylation status of CpG islands in the human brain. | Q50717341 |
| | Transcriptome-wide mapping of N(6)-methyladenosine by m(6)A-seq based on immunocapturing and massively parallel sequencing. | Q51534536 |
| | m6ASNP: a tool for annotating genetic variants by m6A function. | Q52607196 |
| | OUP accepted manuscript | Q60174784 |
| | Global analysis of N6-methyladenosine functions and its disease association using deep learning and network-based methods | Q61451737 |
| | DRUM: Inference of Disease-Associated mA RNA Methylation Sites From a Multi-Layer Heterogeneous Network | Q64079753 |
| | WHISTLE: a high-accuracy map of the human N6-methyladenosine (m6A) epitranscriptome predicted using a machine learning approach | Q64230165 |
| | trumpet: transcriptome-guided quality assessment of m6A-seq data. | Q64976676 |
| | m7GHub: deciphering the location, regulation and pathogenesis of internal mRNA N7-methylguanosine (m7G) sites in human | Q90260055 |
| | PIANO: A Web Server for Pseudouridine-Site (Ψ) Identification and Functional Annotation | Q90745788 |
| | Long non-coding RNA transcriptome of uncharacterized samples can be accurately imputed using protein-coding genes | Q91111171 |
| | The RNA N6-methyladenosine modification landscape of human fetal tissues | Q91624848 |
| | Altered m6A Modification of Specific Cellular Transcripts Affects Flaviviridae Infection | Q91764990 |
| | RNA methylomes reveal the m6A-mediated regulation of DNA demethylase gene SlDML2 in tomato fruit ripening | Q92457929 |
| | LITHOPHONE: Improving lncRNA Methylation Site Prediction Using an Ensemble Predictor | Q96686276 |
| | WITMSG: Large-scale Prediction of Human Intronic m6A RNA Methylation Sites from Sequence and Genomic Features | Q97519259 |
| | N6-methyladenosine in nuclear RNA is a major substrate of the obesity-associated FTO | Q24293481 |
| | Topology of the human and mouse m6A RNA methylomes revealed by m6A-seq | Q24320240 |
| | Comprehensive analysis of mRNA methylation reveals enrichment in 3' UTRs and near stop codons | Q24598126 |
| | Structural basis of N(6)-adenosine methylation by the METTL3-METTL14 complex | Q27709350 |
| | Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources | Q27860739 |
| | Arginine methylation inhibits the binding of proline-rich ligands to Src homology 3, but not WW, domains | Q28140712 |
| | Stem cells. m6A mRNA methylation facilitates resolution of naïve pluripotency toward differentiation | Q28511267 |
| | RNA-methylation-dependent RNA processing controls the speed of the circadian clock | Q28591141 |
| | Regularization Paths for Generalized Linear Models via Coordinate Descent | Q29614491 |
| | Predicting CpG methylation levels by integrating Infinium HumanMethylation450 BeadChip array data | Q31049665 |
| | Predicting the impact of non-coding variants on DNA methylation | Q33878882 |
| | Prediction of methylated CpGs in DNA sequences using a support vector machine | Q34437941 |
| | Predicting the human epigenome from DNA motifs | Q34439703 |
| | Computational prediction of methylation status in human genomic sequences | Q34771158 |
| | Predicting genome-wide DNA methylation using methylation marks, genomic position, and DNA regulatory elements | Q35319065 |
| | Predicting DNA Methylation State of CpG Dinucleotide Using Genome Topological Features and Deep Networks | Q36501173 |
| | SRAMP: prediction of mammalian N6-methyladenosine (m6A) sites based on sequence-derived features | Q36958992 |
| | Gene expression regulation mediated through reversible m⁶A RNA methylation | Q38198852 |
| | Detecting N6-methyladenosine sites from RNA transcriptomes using ensemble Support Vector Machines | Q41353622 |
| | MeT-DB V2.0: elucidating context-specific functions of N6-methyl-adenosine methyltranscriptome. | Q46008109 |
| | MODOMICS: a database of RNA modification pathways. 2017 update | Q46268159 |
| | RMBase v2.0: deciphering the map of RNA modifications from epitranscriptome sequencing data | Q46282727 |
| | RNA methylation and diseases: experimental results, databases, Web servers and computational models | Q47429144 |
| P275 | copyright license | Creative Commons Attribution-NonCommercial 4.0 International | Q34179348 |
| P6216 | copyright status | copyrighted | Q50423863 |
| P304 | page(s) | 1176934320915707 | |
| P577 | publication date | 2020-07-20 | |
| P1433 | published in | Evolutionary Bioinformatics | Q5418673 |
| P1476 | title | Prediction of RNA Methylation Status From Gene Expression Data Using Classification and Regression Methods | |
| P478 | volume | 16 | |