Deepm5C: A deep-learning-based hybrid framework for identifying human RNA N5-methylcytosine sites using a stacking strategy

THRONE: A New Approach for Accurate Prediction of Human RNA N7-Methylguanosine Sites

(2022) Watshara Shoombuatong et al.   JOURNAL OF MOLECULAR BIOLOGY

m5Cpred-XS: A New Method for Predicting RNA m5C Sites Based on XGBoost and SHAP

(2022) Yinbo Liu et al.   Frontiers in Genetics

Post-Transcriptional Modifications of Conserved Nucleotides in the T-Loop of tRNA: A Tale of Functional Convergent Evolution

(2021) Martine Roovers et al.   Genes

iDHS-Deep: an integrated tool for predicting DNase I hypersensitive sites by deep neural network

(2021) Fu-Ying Dao et al.   BRIEFINGS IN BIOINFORMATICS

Conservation of Archaeal C/D Box sRNA-Guided RNA Modifications

(2021) Ruth Breuer et al.   Frontiers in Microbiology

Alteration of mRNA 5-Methylcytosine Modification in Neurons After OGD/R and Potential Roles in Cell Stress Response and Apoptosis

(2021) Huan Jian et al.   Frontiers in Genetics

StackIL6: a stacking ensemble model for improving the prediction of IL-6 inducing peptides

(2021) Phasit Charoenkwan et al.   BRIEFINGS IN BIOINFORMATICS

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

(2021) Fuyi Li et al.   BRIEFINGS IN BIOINFORMATICS

Detection of transcription factors binding to methylated DNA by deep recurrent neural network

(2021) Hongfei Li et al.   BRIEFINGS IN BIOINFORMATICS

m5C-Atlas: a comprehensive database for decoding and annotating the 5-methylcytosine (m5C) epitranscriptome

(2021) Jiongming Ma et al.   NUCLEIC ACIDS RESEARCH

BioSeq-BLM: a platform for analyzing DNA, RNA and protein sequences based on biological language models

(2021) Hong-Liang Li et al.   NUCLEIC ACIDS RESEARCH

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

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

Machine intelligence in peptide therapeutics: A next‐generation tool for rapid disease screening

(2020) Shaherin Basith et al.   MEDICINAL RESEARCH REVIEWS

i6mA-Fuse: improved and robust prediction of DNA 6 mA sites in the Rosaceae genome by fusing multiple feature representation

(2020) Md. Mehedi Hasan et al.   PLANT MOLECULAR BIOLOGY

6mA-RicePred: A Method for Identifying DNA N6-Methyladenine Sites in the Rice Genome Based on Feature Fusion

(2020) Qianfei Huang et al.   Frontiers in Plant Science

HLPpred-Fuse: improved and robust prediction of hemolytic peptide and its activity by fusing multiple feature representation

(2020) Md Mehedi Hasan et al.   BIOINFORMATICS

Computational prediction and interpretation of both general and specific types of promoters in Escherichia coli by exploiting a stacked ensemble-learning framework

(2020) Fuyi Li et al.   BRIEFINGS IN BIOINFORMATICS

The emerging role of RNA modifications in the regulation of mRNA stability

(2020) Sung Ho Boo et al.   EXPERIMENTAL AND MOLECULAR MEDICINE

DeepVF: a deep learning-based hybrid framework for identifying virulence factors using the stacking strategy

(2020) Ruopeng Xie et al.   BRIEFINGS IN BIOINFORMATICS

Epigenomic analysis of Parkinson’s disease neurons identifies Tet2 loss as neuroprotective

(2020) Lee L. Marshall et al.   NATURE NEUROSCIENCE

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

(2020) Yujiao Tang et al.   NUCLEIC ACIDS RESEARCH

RMDisease: a database of genetic variants that affect RNA modifications, with implications for epitranscriptome pathogenesis

(2020) Kunqi Chen et al.   NUCLEIC ACIDS RESEARCH

Prediction of m5C Modifications in RNA Sequences by Combining Multiple Sequence Features

(2020) Lijun Dou et al.   Molecular Therapy-Nucleic Acids

Advances in RNA cytosine-5 methylation: detection, regulatory mechanisms, biological functions and links to cancer

(2020) Chen Xue et al.   Biomarker Research

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

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

Empirical Comparison and Analysis of Web-Based DNA N4-Methylcytosine Site Prediction Tools

(2020) Balachandran Manavalan et al.   Molecular Therapy-Nucleic Acids

i6mA-Pred: Identifying DNA N6-methyladenine sites in the rice genome

(2019) Wei Chen et al.   BIOINFORMATICS

Eukaryotic 5-methylcytosine (m5C) RNA Methyltransferases: Mechanisms, Cellular Functions, and Links to Disease

(2019) Katherine Bohnsack et al.   Genes

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

(2019) Zhao-Chun Xu et al.   BIOINFORMATICS

Advance in predicting subcellular localization of multi-label proteins and its implication for developing multi-target drugs

(2019) Kuo-Chen Chou   CURRENT MEDICINAL CHEMISTRY

DRUM: Inference of Disease-Associated m6A RNA Methylation Sites From a Multi-Layer Heterogeneous Network

(2019) Yujiao Tang et al.   Frontiers in Genetics

Meta-4mCpred: A Sequence-Based Meta-Predictor for Accurate DNA 4mC Site Prediction Using Effective Feature Representation

(2019) Balachandran Manavalan et al.   Molecular Therapy-Nucleic Acids

DeepCleave: a deep learning predictor for caspase and matrix metalloprotease substrates and cleavage sites

(2019) Fuyi Li et al.   BIOINFORMATICS

BioSeq-Analysis2.0: an updated platform for analyzing DNA, RNA and protein sequences at sequence level and residue level based on machine learning approaches

(2019) Bin Liu et al.   NUCLEIC ACIDS RESEARCH

iDNA6mA-Rice: A Computational Tool for Detecting N6-Methyladenine Sites in Rice

(2019) Hao Lv et al.   Frontiers in Genetics

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

i4mC-ROSE, a bioinformatics tool for the identification of DNA N4-methylcytosine sites in the Rosaceae genome

(2019) Md. Mehedi Hasan et al.   INTERNATIONAL JOURNAL OF BIOLOGICAL MACROMOLECULES

SDM6A: A Web-Based Integrative Machine-Learning Framework for Predicting 6mA Sites in the Rice Genome

(2019) Shaherin Basith et al.   Molecular Therapy-Nucleic Acids

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

iDNA6mA-PseKNC: Identifying DNA N 6 -methyladenosine sites by incorporating nucleotide physicochemical properties into PseKNC

(2018) Pengmian Feng et al.   GENOMICS

Transcriptome-Wide Annotation of m5C RNA Modifications Using Machine Learning

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

A Leveraged Signal-to-Noise Ratio (LSTNR) Method to Extract Differentially Expressed Genes and Multivariate Patterns of Expression From Noisy and Low-Replication RNAseq Data

(2018) Oswaldo A. Lozoya et al.   Frontiers in Genetics

CPPred-FL: a sequence-based predictor for large-scale identification of cell-penetrating peptides by feature representation learning

(2018) Xiaoli Qiang et al.   BRIEFINGS IN BIOINFORMATICS

OUP accepted manuscript

(2018)   BRIEFINGS IN BIOINFORMATICS

Deep learning for biology

(2018) Sarah Webb   NATURE

mAHTPred: a sequence-based meta-predictor for improving the prediction of anti-hypertensive peptides using effective feature representation

(2018) Balachandran Manavalan et al.   BIOINFORMATICS

A brief survey of machine learning methods in protein sub-Golgi localization

(2018) Wuritu Yang et al.   Current Bioinformatics

RNAm5Cfinder: A Web-server for Predicting RNA 5-methylcytosine (m5C) Sites Based on Random Forest

(2018) Jianwei Li et al.   Scientific Reports

iRNAm5C-PseDNC: identifying RNA 5-methylcytosine sites by incorporating physical-chemical properties into pseudo dinucleotide composition

(2017) Wang-Ren Qiu et al.   Oncotarget

PHYPred: a tool for identifying bacteriophage enzymes and hydrolases

(2016) Hui Ding et al.   VIROLOGICA SINICA

iEnhancer-2L: a two-layer predictor for identifying enhancers and their strength by pseudok-tuple nucleotide composition

(2015) Bin Liu et al.   BIOINFORMATICS

Pseudo nucleotide composition or PseKNC: an effective formulation for analyzing genomic sequences

(2015) Wei Chen et al.   Molecular BioSystems

Eukaryotic rRNA Modification by Yeast 5-Methylcytosine-Methyltransferases and Human Proliferation-Associated Antigen p120

(2015) Gabrielle Bourgeois et al.   PLoS One