DNN-m6A: A Cross-Species Method for Identifying RNA N6-methyladenosine Sites Based on Deep Neural Network with Multi-Information Fusion

Epigenetically upregulated oncoprotein PLCE1 drives esophageal carcinoma angiogenesis and proliferation via activating the PI-PLCε-NF-κB signaling pathway and VEGF-C/ Bcl-2 expression

(2019) Yunzhao Chen et al.   Molecular Cancer

Identifying N6-methyladenosine sites using extreme gradient boosting system optimized by particle swarm optimizer

(2019) Xiaowei Zhao et al.   JOURNAL OF THEORETICAL BIOLOGY

Single-base mapping of m6A by an antibody-independent method

(2019) Zhang Zhang et al.   Science Advances

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

4mCpred-EL: An Ensemble Learning Framework for Identification of DNA N4-methylcytosine Sites in the Mouse Genome

(2019) Manavalan et al.   Cells

RNAm5CPred: Prediction of RNA 5-Methylcytosine Sites Based on Three Different Kinds of Nucleotide Composition

(2019) Ting Fang et al.   Molecular Therapy-Nucleic Acids

Accurate RNA 5-methylcytosine site prediction based on heuristic physical-chemical properties reduction and classifier ensemble

(2018) Ming Zhang et al.   ANALYTICAL BIOCHEMISTRY

iMethyl-STTNC: Identification of N 6 -methyladenosine sites by extending the Idea of SAAC into Chou's PseAAC to formulate RNA sequences

(2018) Shahid Akbar et al.   JOURNAL OF THEORETICAL BIOLOGY

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

(2018) Xiaofeng Wang et al.   PLANT MOLECULAR BIOLOGY

M6APred-EL: A sequence-based predictor for identifying N6-methyladenosine sites using ensemble learning

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

iRNA(m6A)-PseDNC: Identifying N6-methyladenosine sites using pseudo dinucleotide composition

(2018) Wei Chen et al.   ANALYTICAL BIOCHEMISTRY

PseUI: Pseudouridine sites identification based on RNA sequence information

(2018) Jingjing He et al.   BMC BIOINFORMATICS

Imbalance learning for the prediction of N6-Methylation sites in mRNAs

(2018) Zhixun Zhao et al.   BMC GENOMICS

Sequence clustering in bioinformatics: an empirical study

(2018) Quan Zou et al.   BRIEFINGS IN BIOINFORMATICS

m6A mRNA methylation regulates AKT activity to promote the proliferation and tumorigenicity of endometrial cancer

(2018) Jun Liu et al.   NATURE CELL BIOLOGY

M6AMRFS: Robust Prediction of N6-Methyladenosine Sites With Sequence-Based Features in Multiple Species

(2018) Xiaoli Qiang et al.   Frontiers in Genetics

A boosted decision tree approach using Bayesian hyper-parameter optimization for credit scoring

(2017) Yufei Xia et al.   EXPERT SYSTEMS WITH APPLICATIONS

iRNA-PseColl: Identifying the Occurrence Sites of Different RNA Modifications by Incorporating Collective Effects of Nucleotides into PseKNC

(2017) Pengmian Feng et al.   Molecular Therapy-Nucleic Acids

Detecting N6-methyladenosine sites from RNA transcriptomes using ensemble Support Vector Machines

(2017) Wei Chen et al.   Scientific Reports

Identifying N6-methyladenosine sites using multi-interval nucleotide pair position specificity and support vector machine

(2017) Pengwei Xing et al.   Scientific Reports

iSS-PC: Identifying Splicing Sites via Physical-Chemical Properties Using Deep Sparse Auto-Encoder

(2017) Zhao-Chun Xu et al.   Scientific Reports

pRNAm-PC: Predicting N6-methyladenosine sites in RNA sequences via physical–chemical properties

(2016) Zi Liu et al.   ANALYTICAL BIOCHEMISTRY

Identifying 2′-O-methylationation sites by integrating nucleotide chemical properties and nucleotide compositions

(2016) Wei Chen et al.   GENOMICS

METTL14 suppresses the metastatic potential of hepatocellular carcinoma by modulatingN6-methyladenosine-dependent primary MicroRNA processing

(2016) Jin-zhao Ma et al.   HEPATOLOGY

TargetM6A: Identifying N6-Methyladenosine Sites From RNA Sequences via Position-Specific Nucleotide Propensities and a Support Vector Machine

(2016) Guang-Qing Li et al.   IEEE TRANSACTIONS ON NANOBIOSCIENCE

Identifying RNA 5-methylcytosine sites via pseudo nucleotide compositions

(2016) Pengmian Feng et al.   Molecular BioSystems

The m 6 A Methyltransferase METTL3 Promotes Translation in Human Cancer Cells

(2016) Shuibin Lin et al.   MOLECULAR CELL

Post-transcriptional gene regulation by mRNA modifications

(2016) Boxuan Simen Zhao et al.   NATURE REVIEWS MOLECULAR CELL BIOLOGY

SRAMP: prediction of mammalian N6-methyladenosine (m6A) sites based on sequence-derived features

(2016) Yuan Zhou et al.   NUCLEIC ACIDS RESEARCH

RNAMethPre: A Web Server for the Prediction and Query of mRNA m6A Sites

(2016) Shunian Xiang et al.   PLoS One

RNA epigenetics

(2015) Nian Liu et al.   Translational Research

iHyd-PseAAC: Predicting Hydroxyproline and Hydroxylysine in Proteins by Incorporating Dipeptide Position-Specific Propensity into Pseudo Amino Acid Composition

(2014) Yan Xu et al.   INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES

Transcriptome-wide mapping of N6-methyladenosine by m6A-seq based on immunocapturing and massively parallel sequencing

(2013) Dan Dominissini et al.   Nature Protocols

Comprehensive Analysis of mRNA Methylation Reveals Enrichment in 3′ UTRs and near Stop Codons

(2012) Kate D. Meyer et al.   CELL

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

(2012) Guanqun Zheng et al.   MOLECULAR CELL

Widespread occurrence of 5-methylcytosine in human coding and non-coding RNA

(2012) Jeffrey E. Squires et al.   NUCLEIC ACIDS RESEARCH

Reversible RNA adenosine methylation in biological regulation

(2012) Guifang Jia et al.   TRENDS IN GENETICS

N6-methyl-adenosine (m6A) in RNA: An Old Modification with A Novel Epigenetic Function

(2012) Yamei Niu et al.   GENOMICS PROTEOMICS & BIOINFORMATICS

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

(2011) Guifang Jia et al.   Nature Chemical Biology

Yeast targets for mRNA methylation

(2010) Zsuzsanna Bodi et al.   NUCLEIC ACIDS RESEARCH

A systematic analysis of performance measures for classification tasks

(2009) Marina Sokolova et al.   INFORMATION PROCESSING & MANAGEMENT