Recent methodology progress of deep learning for RNA–protein interaction prediction

Construction of Complex Features for Computational Predicting ncRNA-Protein Interaction

(2019) Qiguo Dai et al.   Frontiers in Genetics

pysster: classification of biological sequences by learning sequence and structure motifs with convolutional neural networks

(2018) Stefan Budach et al.   BIOINFORMATICS

Predicting RNA–protein binding sites and motifs through combining local and global deep convolutional neural networks

(2018) Xiaoyong Pan et al.   BIOINFORMATICS

OUP accepted manuscript

(2018)   BIOINFORMATICS

Prediction of RNA-protein sequence and structure binding preferences using deep convolutional and recurrent neural networks

(2018) Xiaoyong Pan et al.   BMC GENOMICS

Opportunities and obstacles for deep learning in biology and medicine

(2018) Travers Ching et al.   Journal of the Royal Society Interface

Feature-Based and String-Based Models for Predicting RNA-Protein Interaction

(2018) Donald Adjeroh et al.   MOLECULES

A brave new world of RNA-binding proteins

(2018) Matthias W. Hentze et al.   NATURE REVIEWS MOLECULAR CELL BIOLOGY

Learning distributed representations of RNA sequences and its application for predicting RNA-protein binding sites with a convolutional neural network

(2018) Xiaoyong Pan et al.   NEUROCOMPUTING

A Deep Learning Framework for Robust and Accurate Prediction of ncRNA-Protein Interactions Using Evolutionary Information

(2018) Hai-Cheng Yi et al.   Molecular Therapy-Nucleic Acids

Motif models for RNA-binding proteins

(2018) Alexander Sasse et al.   CURRENT OPINION IN STRUCTURAL BIOLOGY

Prediction of RNA-protein interactions using conjoint triad feature and chaos game representation

(2018) Hongchu Wang et al.   Bioengineered

Prediction of RNA-protein interactions by combining deep convolutional neural network with feature selection ensemble method

(2018) Lei Wang et al.   JOURNAL OF THEORETICAL BIOLOGY

Accurate Prediction of ncRNA-Protein Interactions From the Integration of Sequence and Evolutionary Information

(2018) Zhao-Hui Zhan et al.   Frontiers in Genetics

Combining High Speed ELM Learning with a Deep Convolutional Neural Network Feature Encoding for Predicting Protein-RNA Interactions

(2018) Lei Wang et al.   IEEE-ACM Transactions on Computational Biology and Bioinformatics

Emerging roles of RNA-binding proteins in diabetes and their therapeutic potential in diabetic complications

(2017) Curtis A. Nutter et al.   Wiley Interdisciplinary Reviews-RNA

Advances and challenges in the detection of transcriptome-wide protein-RNA interactions

(2017) Emily C. Wheeler et al.   Wiley Interdisciplinary Reviews-RNA

RCK: accurate and efficient inference of sequence- and structure-based protein–RNA binding models from RNAcompete data

(2016) Yaron Orenstein et al.   BIOINFORMATICS

Orthogonal matrix factorization enables integrative analysis of multiple RNA binding proteins

(2016) Martin Stražar et al.   BIOINFORMATICS

IPMiner: hidden ncRNA-protein interaction sequential pattern mining with stacked autoencoder for accurate computational prediction

(2016) Xiaoyong Pan et al.   BMC GENOMICS

rpiCOOL: A tool for In Silico RNA–protein interaction detection using random forest

(2016) Mohammad Akbaripour-Elahabad et al.   JOURNAL OF THEORETICAL BIOLOGY

Robust transcriptome-wide discovery of RNA-binding protein binding sites with enhanced CLIP (eCLIP)

(2016) Eric L Van Nostrand et al.   NATURE METHODS

DanQ: a hybrid convolutional and recurrent deep neural network for quantifying the function of DNA sequences

(2016) Daniel Quang et al.   NUCLEIC ACIDS RESEARCH

CLIPdb: a CLIP-seq database for protein-RNA interactions

(2015) Yu-Cheng T Yang et al.   BMC GENOMICS

Deep learning

(2015) Yann LeCun et al.   NATURE

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

(2015) Babak Alipanahi et al.   NATURE BIOTECHNOLOGY

RPI-Pred: predicting ncRNA-protein interaction using sequence and structural information

(2015) V. Suresh et al.   NUCLEIC ACIDS RESEARCH

The MEME Suite

(2015) Timothy L. Bailey et al.   NUCLEIC ACIDS RESEARCH

A deep learning framework for modeling structural features of RNA-binding protein targets

(2015) Sai Zhang et al.   NUCLEIC ACIDS RESEARCH

Computationally predicting protein-RNA interactions using only positive and unlabeled examples

(2015) Zhanzhan Cheng et al.   Journal of Bioinformatics and Computational Biology

DoRiNA 2.0—upgrading the doRiNA database of RNA interactions in post-transcriptional regulation

(2014) Kai Blin et al.   NUCLEIC ACIDS RESEARCH

GraphProt: modeling binding preferences of RNA-binding proteins

(2014) Daniel Maticzka et al.   GENOME BIOLOGY

catRAPID omics: a web server for large-scale prediction of protein-RNA interactions

(2013) F. Agostini et al.   BIOINFORMATICS

starBase v2.0: decoding miRNA-ceRNA, miRNA-ncRNA and protein–RNA interaction networks from large-scale CLIP-Seq data

(2013) Jun-Hao Li et al.   NUCLEIC ACIDS RESEARCH

TDP-43 and FUS RNA-binding Proteins Bind Distinct Sets of Cytoplasmic Messenger RNAs and Differently Regulate Their Post-transcriptional Fate in Motoneuron-like Cells

(2012) Claudia Colombrita et al.   JOURNAL OF BIOLOGICAL CHEMISTRY

Predicting RNA-Protein Interactions Using Only Sequence Information

(2011) Usha K Muppirala et al.   BMC BIOINFORMATICS

RNA–protein interactions in human health and disease

(2011) Ahmad M. Khalil et al.   SEMINARS IN CELL & DEVELOPMENTAL BIOLOGY

Identification of RNA-protein interaction networks using PAR-CLIP

(2011) Manuel Ascano et al.   Wiley Interdisciplinary Reviews-RNA

PARalyzer: definition of RNA binding sites from PAR-CLIP short-read sequence data

(2011) David L Corcoran et al.   GENOME BIOLOGY

RNAcontext: A New Method for Learning the Sequence and Structure Binding Preferences of RNA-Binding Proteins

(2010) Hilal Kazan et al.   PLoS Computational Biology

Argonaute HITS-CLIP decodes microRNA–mRNA interaction maps

(2009) Sung Wook Chi et al.   NATURE