Prediction of DNA binding proteins using local features and long-term dependencies with primary sequences based on deep learning

HMMPred: Accurate Prediction of DNA-Binding Proteins Based on HMM Profiles and XGBoost Feature Selection

(2020) Xiuzhi Sang et al.   Computational and Mathematical Methods in Medicine

PredDBP-Stack: Prediction of DNA-Binding Proteins from HMM Profiles using a Stacked Ensemble Method

(2020) Jun Wang et al.   Biomed Research International

A high-performance approach for predicting donor splice sites based on short window size and imbalanced large samples

(2019) Ying Zeng et al.   Biology Direct

DP-BINDER: machine learning model for prediction of DNA-binding proteins by fusing evolutionary and physicochemical information

(2019) Farman Ali et al.   JOURNAL OF COMPUTER-AIDED MOLECULAR DESIGN

MsDBP: Exploring DNA-Binding Proteins by Integrating Multiscale Sequence Information via Chou’s Five-Step Rule

(2019) Xiuquan Du et al.   JOURNAL OF PROTEOME RESEARCH

DeepSite: bidirectional LSTM and CNN models for predicting DNA–protein binding

(2019) Yongqing Zhang et al.   International Journal of Machine Learning and Cybernetics

An improved deep learning method for predicting DNA-binding proteins based on contextual features in amino acid sequences

(2019) Siquan Hu et al.   PLoS One

pLoc_bal-mAnimal: predict subcellular localization of animal proteins by balancing training dataset and PseAAC

(2018) Xiang Cheng et al.   BIOINFORMATICS

StackDPPred: A Stacking based Prediction of DNA-binding Protein from Sequence

(2018) Avdesh Mishra et al.   BIOINFORMATICS

DPP-PseAAC: A DNA-binding protein prediction model using Chou’s general PseAAC

(2018) M. Saifur Rahman et al.   JOURNAL OF THEORETICAL BIOLOGY

Vehicle Detection and Counting in High-Resolution Aerial Images Using Convolutional Regression Neural Network

(2018) Hilal Tayara et al.   IEEE Access

DBPPred-PDSD: Machine learning approach for prediction of DNA-binding proteins using Discrete Wavelet Transform and optimized integrated features space

(2018) Farman Ali et al.   CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS

pLoc_bal-mHum: Predict subcellular localization of human proteins by PseAAC and quasi-balancing training dataset

(2018) Kuo-Chen Chou et al.   GENOMICS

A Model Stacking Framework for Identifying DNA Binding Proteins by Orchestrating Multi-View Features and Classifiers

(2018) Xiu-Juan Liu et al.   Genes

Object Detection in Very High-Resolution Aerial Images Using One-Stage Densely Connected Feature Pyramid Network

(2018) Hilal Tayara et al.   SENSORS

iKcr-PseEns: Identify lysine crotonylation sites in histone proteins with pseudo components and ensemble classifier

(2017) Wang-Ren Qiu et al.   GENOMICS

Local-DPP: An improved DNA-binding protein prediction method by exploring local evolutionary information

(2017) Leyi Wei et al.   INFORMATION SCIENCES

PSFM-DBT: Identifying DNA-Binding Proteins by Combing Position Specific Frequency Matrix and Distance-Bigram Transformation

(2017) et al.   INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES

iDNAProt-ES: Identification of DNA-binding Proteins Using Evolutionary and Structural Features

(2017) Shahana Yasmin Chowdhury et al.   Scientific Reports

HMMBinder: DNA-Binding Protein Prediction Using HMM Profile Based Features

(2017) Rianon Zaman et al.   Biomed Research International

On the prediction of DNA-binding proteins only from primary sequences: A deep learning approach

(2017) Yu-Hui Qu et al.   PLoS One

Convolutional neural network architectures for predicting DNA–protein binding

(2016) Haoyang Zeng et al.   BIOINFORMATICS

BindUP: a web server for non-homology-based prediction of DNA and RNA binding proteins

(2016) Inbal Paz et al.   NUCLEIC ACIDS RESEARCH

iRNA-AI: identifying the adenosine to inosine editing sites in RNA sequences

(2016) Wei Chen et al.   Oncotarget

DNABP: Identification of DNA-Binding Proteins Based on Feature Selection Using a Random Forest and Predicting Binding Residues

(2016) Xin Ma et al.   PLoS One

Identifying DNA-binding proteins by combining support vector machine and PSSM distance transformation

(2015) Ruifeng Xu et al.   BMC Systems Biology

Predicting the sequence specificities of DNA- and RNA-binding proteins by deep learning

(2015) Babak Alipanahi et al.   NATURE BIOTECHNOLOGY

newDNA-Prot: Prediction of DNA-binding proteins by employing support vector machine and a comprehensive sequence representation

(2014) Yanping Zhang et al.   COMPUTATIONAL BIOLOGY AND CHEMISTRY

PseDNA-Pro: DNA-Binding Protein Identification by Combining Chou’s PseAAC and Physicochemical Distance Transformation

(2014) Bin Liu et al.   Molecular Informatics

Sequence Based Prediction of DNA-Binding Proteins Based on Hybrid Feature Selection Using Random Forest and Gaussian Naïve Bayes

(2014) Wangchao Lou et al.   PLoS One

iDNA-Prot|dis: Identifying DNA-Binding Proteins by Incorporating Amino Acid Distance-Pairs and Reduced Alphabet Profile into the General Pseudo Amino Acid Composition

(2014) Bin Liu et al.   PLoS One

An improved sequence based prediction protocol for DNA-binding proteins using SVM and comprehensive feature analysis

(2013) Chuanxin Zou et al.   BMC BIOINFORMATICS

DNA-Prot: Identification of DNA Binding Proteins from Protein Sequence Information using Random Forest

(2012) K. Krishna. Kumar et al.   JOURNAL OF BIOMOLECULAR STRUCTURE & DYNAMICS

Reorganizing the protein space at the Universal Protein Resource (UniProt)

(2011)   NUCLEIC ACIDS RESEARCH

NAPS: a residue-level nucleic acid-binding prediction server

(2010) Matthew B. Carson et al.   NUCLEIC ACIDS RESEARCH

Prediction of DNA-binding residues in proteins from amino acid sequences using a random forest model with a hybrid feature

(2008) Jiansheng Wu et al.   BIOINFORMATICS