Deep-4mCGP: A Deep Learning Approach to Predict 4mC Sites in Geobacter pickeringii by Using Correlation-Based Feature Selection Technique

Screening of Prospective Plant Compounds as H1R and CL1R Inhibitors and Its Antiallergic Efficacy through Molecular Docking Approach

(2021) Hasan Zulfiqar et al.   Computational and Mathematical Methods in Medicine

iBLP: An XGBoost-Based Predictor for Identifying Bioluminescent Proteins

(2021) Dan Zhang et al.   Computational and Mathematical Methods in Medicine

CSBPI_Site：Multi-Information Sources of Features to RNA Binding Sites Prediction

(2021) Lichao Zhang et al.   Current Bioinformatics

sgRNACNN: identifying sgRNA on-target activity in four crops using ensembles of convolutional neural networks

(2021) Mengting Niu et al.   PLANT MOLECULAR BIOLOGY

A sequence-based deep learning approach to predict CTCF-mediated chromatin loop

(2021) Hao Lv et al.   BRIEFINGS IN BIOINFORMATICS

Effective Classification of Melting Curve in Real-Time PCR based on Dynamic Filter-based Convolutional Neural Network

(2021) Di Gai et al.   Current Bioinformatics

Prediction of Protein-protein Interactions in Arabidopsis Thaliana using Partial Training Samples in a Machine Learning Framework

(2021) Fee Faysal Ahmed et al.   Current Bioinformatics

PPD: A Manually Curated Database for Experimentally Verified Prokaryotic Promoters

(2021) Wei Su et al.   JOURNAL OF MOLECULAR BIOLOGY

NeuroPred-FRL: an interpretable prediction model for identifying neuropeptide using feature representation learning

(2021) Md Mehedi Hasan et al.   BRIEFINGS IN BIOINFORMATICS

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

(2021) Phasit Charoenkwan et al.   BRIEFINGS IN BIOINFORMATICS

Identification of Potential Inhibitors against SARS-Cov-2 using Computational Drug Repurposing Study

(2021) Hasan Zulfiqar et al.   Current Bioinformatics

Deep-4mCW2V: A sequence-based predictor to identify N4-methylcytosine sites in Escherichia coli

(2021) Hasan Zulfiqar et al.   METHODS

RFhy-m2G: Identification of RNA N2-methylguanosine modification sites based on random forest and hybrid features

(2021) Chunyan Ao et al.   METHODS

DNA4mC-LIP: a linear integration method to identify N4-methylcytosine site in multiple species

(2020) Qiang Tang et al.   BIOINFORMATICS

Extremely-randomized-tree-based prediction of N6-methyladenosine Sites in Saccharomyces cerevisiae

(2020) Rajiv Gandhi Govindaraj et al.   CURRENT GENOMICS

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

(2020) Md Mehedi Hasan et al.   BIOINFORMATICS

Integrated Analysis of mRNA-seq and miRNA-seq to Identify c-MYC, YAP1 and miR-3960 as Major Players in the Anticancer Effects of Caffeic Acid Phenethyl ester in Human Small Cell Lung Cancer Cell Line

(2020) Fei Mo et al.   CURRENT GENE THERAPY

DeepTorrent: a deep learning-based approach for predicting DNA N4-methylcytosine sites

(2020) Quanzhong Liu et al.   BRIEFINGS IN BIOINFORMATICS

An Unbiased Predictive Model to Detect DNA Methylation Propensity of CpG Islands in the Human Genome

(2020) Dicle Yalcin et al.   Current Bioinformatics

PoGB-Pred: Prediction of Antifreeze Proteins Sequences using Amino Acid Composition with Feature Selection followed by a Sequential based Ensemble Approach

(2020) Affan Alim et al.   Current Bioinformatics

Deep-BSC: Predicting Raw DNA Binding Pattern in Arabidopsis thaliana

(2020) Syed Adnan Shah Bukhari et al.   Current Bioinformatics

A Review on the Application of Deep Learning in Bioinformatics

(2020) Yongqing Zhang et al.   Current Bioinformatics

PsePSSM-based Prediction for the Protein-ATP Binding Sites

(2020) Li Qian et al.   Current Bioinformatics

Prediction of bio-sequence modifications and the associations with diseases

(2020) Chunyan Ao et al.   Briefings in Functional Genomics

Protein Secondary Structure Prediction Using Character Bi-gram Embedding and Bi-LSTM

(2020) Ashish Kumar Sharma et al.   Current Bioinformatics

Iterative feature representations improve N4-methylcytosine site prediction

(2019) Leyi Wei et al.   BIOINFORMATICS

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

Prediction of neddylation sites using the composition of k-spaced amino acid pairs and fuzzy SVM

(2019) Zhe Ju et al.   Current Bioinformatics

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

(2019) Manavalan et al.   Cells

Electroencephalography Based Fusion Two-Dimensional (2D)-Convolution Neural Networks (CNN) Model for Emotion Recognition System

(2018) Yea-Hoon Kwon et al.   SENSORS

4mCPred: Machine Learning Methods for DNA N4-methylcytosine sites Prediction

(2018) Wenying He et al.   BIOINFORMATICS

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

(2018) Wuritu Yang et al.   Current Bioinformatics

ProLanGO: Protein Function Prediction Using Neural Machine Translation Based on a Recurrent Neural Network

(2017) Renzhi Cao et al.   MOLECULES

MethSMRT: an integrative database for DNA N6-methyladenine and N4-methylcytosine generated by single-molecular real-time sequencing

(2016) Pohao Ye et al.   NUCLEIC ACIDS RESEARCH

3-methylcytosine in cancer: an underappreciated methyl lesion?

(2016) Thomas Pataillot-Meakin et al.   Epigenomics

Function and information content of DNA methylation

(2015) Dirk Schübeler   NATURE

Exploring genome wide bisulfite sequencing for DNA methylation analysis in livestock: a technical assessment

(2014) Rachael Doherty et al.   Frontiers in Genetics

DNA methylation: roles in mammalian development

(2013) Zachary D. Smith et al.   NATURE REVIEWS GENETICS

XanthomonasAvrBs3 Family-Type III Effectors: Discovery and Function

(2010) Jens Boch et al.   Annual Review of Phytopathology

Direct detection of DNA methylation during single-molecule, real-time sequencing

(2010) Benjamin A Flusberg et al.   NATURE METHODS