Prediction of Multiple Types of RNA Modifications via Biological Language Model

RBP-TSTL is a two-stage transfer learning framework for genome-scale prediction of RNA-binding proteins

(2022) Xinxin Peng et al.   BRIEFINGS IN BIOINFORMATICS

DNABERT: pre-trained Bidirectional Encoder Representations from Transformers model for DNA-language in genome

(2021) Yanrong Ji et al.   BIOINFORMATICS

A transformer architecture based on BERT and 2D convolutional neural network to identify DNA enhancers from sequence information

(2021) Nguyen Quoc Khanh Le et al.   BRIEFINGS IN BIOINFORMATICS

MG-BERT: leveraging unsupervised atomic representation learning for molecular property prediction

(2021) Xiao-Chen Zhang et al.   BRIEFINGS IN BIOINFORMATICS

Weakly supervised learning of RNA modifications from low-resolution epitranscriptome data

(2021) Daiyun Huang et al.   BIOINFORMATICS

Leveraging the attention mechanism to improve the identification of DNA N6-methyladenine sites

(2021) Ying Zhang et al.   BRIEFINGS IN BIOINFORMATICS

Porpoise: a new approach for accurate prediction of RNA pseudouridine sites

(2021) Fuyi Li et al.   BRIEFINGS IN BIOINFORMATICS

Attention-based multi-label neural networks for integrated prediction and interpretation of twelve widely occurring RNA modifications

(2021) Zitao Song et al.   Nature Communications

Staem5: A novel computational approach for accurate prediction of m5C site

(2021) Di Chai et al.   Molecular Therapy-Nucleic Acids

iMRM:a platform for simultaneously identifying multiple kinds of RNA modifications

(2020) Kewei Liu et al.   BIOINFORMATICS

m7GHub: deciphering the location, regulation and pathogenesis of internal mRNA N7-methylguanosine (m7G) sites in human

(2020) Bowen Song et al.   BIOINFORMATICS

iMethyl-Deep: N6 Methyladenosine Identification of Yeast Genome with Automatic Feature Extraction Technique by Using Deep Learning Algorithm

(2020) Omid Mahmoudi et al.   Genes

iRNA5hmC: The First Predictor to Identify RNA 5-Hydroxymethylcytosine Modifications Using Machine Learning

(2020) Yuan Liu et al.   Frontiers in Bioengineering and Biotechnology

m6A-Atlas: a comprehensive knowledgebase for unraveling the N6-methyladenosine (m6A) epitranscriptome

(2020) Yujiao Tang et al.   NUCLEIC ACIDS RESEARCH

An Interpretable Prediction Model for Identifying N7-Methylguanosine Sites Based on XGBoost and SHAP

(2020) Yue Bi et al.   Molecular Therapy-Nucleic Acids

Identification of D Modification Sites by Integrating Heterogeneous Features in Saccharomyces cerevisiae

(2019) Pengmian Feng et al.   MOLECULES

iRNAD: a computational tool for identifying D modification sites in RNA sequence

(2019) Zhao-Chun Xu et al.   BIOINFORMATICS

Comprehensive review and assessment of computational methods for predicting RNA post-transcriptional modification sites from RNA sequences

(2019) Zhen Chen et al.   BRIEFINGS IN BIOINFORMATICS

RFAthM6A: a new tool for predicting m6A sites in Arabidopsis thaliana

(2018) Xiaofeng Wang et al.   PLANT MOLECULAR BIOLOGY

Transcriptome-Wide Annotation of m5C RNA Modifications Using Machine Learning

(2018) Jie Song et al.   Frontiers in Plant Science

iRNA-3typeA: Identifying Three Types of Modification at RNA’s Adenosine Sites

(2018) Wei Chen et al.   Molecular Therapy-Nucleic Acids

BERMP: a cross-species classifier for predicting m6A sites by integrating a deep learning algorithm and a random forest approach

(2018) Yu Huang et al.   International Journal of Biological Sciences

DeepM6ASeq: prediction and characterization of m6A-containing sequences using deep learning

(2018) Yiqian Zhang et al.   BMC BIOINFORMATICS

Gene2vec: gene subsequence embedding for prediction of mammalian N6-methyladenosine sites from mRNA

(2018) Quan Zou et al.   RNA

RMBase v2.0: deciphering the map of RNA modifications from epitranscriptome sequencing data

(2017) Jia-Jia Xuan et al.   NUCLEIC ACIDS RESEARCH

Ensembl Genomes 2018: an integrated omics infrastructure for non-vertebrate species

(2017) Paul Julian Kersey et al.   NUCLEIC ACIDS RESEARCH

m6AVar: a database of functional variants involved in m6A modification

(2017) Yueyuan Zheng et al.   NUCLEIC ACIDS RESEARCH

MODOMICS: a database of RNA modification pathways. 2017 update

(2017) Pietro Boccaletto et al.   NUCLEIC ACIDS RESEARCH

Transcriptome-Wide Mapping of RNA 5-Methylcytosine in Arabidopsis mRNAs and Noncoding RNAs

(2017) Rakesh David et al.   PLANT CELL

Messenger RNA modifications: Form, distribution, and function

(2016) W. V. Gilbert et al.   SCIENCE

RAMPred: identifying the N1-methyladenosine sites in eukaryotic transcriptomes

(2016) Wei Chen et al.   Scientific Reports

The Genomic Landscape and Clinical Relevance of A-to-I RNA Editing in Human Cancers

(2015) Leng Han et al.   CANCER CELL

m6A RNA Methylation Is Regulated by MicroRNAs and Promotes Reprogramming to Pluripotency

(2015) Tong Chen et al.   Cell Stem Cell

Autophagy in spinal motor neurons of conditional ADAR2-knockout mice: An implication for a role of calcium in increased autophagy flux in ALS

(2015) Soichi Sasaki et al.   NEUROSCIENCE LETTERS

An expanding universe of mRNA modifications

(2014) Samie R Jaffrey   NATURE STRUCTURAL & MOLECULAR BIOLOGY

Internal mRNA Methylation Finally Finds Functions

(2014) T. W. Nilsen   SCIENCE

A Pseudouridine Residue in the Spliceosome Core Is Part of the Filamentous Growth Program in Yeast

(2014) Anindita Basak et al.   Cell Reports

Methionine Adenosyltransferase 2B, HuR, and Sirtuin 1 Protein Cross-talk Impacts on the Effect of Resveratrol on Apoptosis and Growth in Liver Cancer Cells

(2013) Heping Yang et al.   JOURNAL OF BIOLOGICAL CHEMISTRY

CD-HIT: accelerated for clustering the next-generation sequencing data

(2012) Limin Fu et al.   BIOINFORMATICS

ALKBH5 Is a Mammalian RNA Demethylase that Impacts RNA Metabolism and Mouse Fertility

(2012) Guanqun Zheng et al.   MOLECULAR CELL

Yeast Rrp8p, a novel methyltransferase responsible for m1A 645 base modification of 25S rRNA

(2012) Christian Peifer et al.   NUCLEIC ACIDS RESEARCH

Deficit of tRNALys modification by Cdkal1 causes the development of type 2 diabetes in mice

(2011) Fan-Yan Wei et al.   JOURNAL OF CLINICAL INVESTIGATION

N6-Methyladenosine in nuclear RNA is a major substrate of the obesity-associated FTO

(2011) Guifang Jia et al.   Nature Chemical Biology

Small nucleolar RNA 42 acts as an oncogene in lung tumorigenesis

(2011) Y-P Mei et al.   ONCOGENE

5-methylcytosine in RNA: detection, enzymatic formation and biological functions

(2009) Yuri Motorin et al.   NUCLEIC ACIDS RESEARCH