Challenges for machine learning in RNA-protein interaction prediction

GraphBind: protein structural context embedded rules learned by hierarchical graph neural networks for recognizing nucleic-acid-binding residues

(2021) Ying Xia et al.   NUCLEIC ACIDS RESEARCH

NPI-GNN: Predicting ncRNA–protein interactions with deep graph neural networks

(2021) Zi-Ang Shen et al.   BRIEFINGS IN BIOINFORMATICS

Biological structure and function emerge from scaling unsupervised learning to 250 million protein sequences

(2021) Alexander Rives et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Graph representation learning in bioinformatics: trends, methods and applications

(2021) Hai-Cheng Yi et al.   BRIEFINGS IN BIOINFORMATICS

Highly accurate protein structure prediction with AlphaFold

(2021) John Jumper et al.   NATURE

Graph Neural Networks and Their Current Applications in Bioinformatics

(2021) Xiao-Meng Zhang et al.   Frontiers in Genetics

Protein–RNA interaction prediction with deep learning: structure matters

(2021) Junkang Wei et al.   BRIEFINGS IN BIOINFORMATICS

The physics of higher-order interactions in complex systems

(2021) Federico Battiston et al.   Nature Physics

Graph neural representational learning of RNA secondary structures for predicting RNA-protein interactions

(2020) Zichao Yan et al.   BIOINFORMATICS

A large-scale binding and functional map of human RNA-binding proteins

(2020) Eric L. Van Nostrand et al.   NATURE

Networks beyond pairwise interactions: Structure and dynamics

(2020) Federico Battiston et al.   PHYSICS REPORTS-REVIEW SECTION OF PHYSICS LETTERS

A gentle introduction to deep learning for graphs

(2020) Davide Bacciu et al.   NEURAL NETWORKS

RNA-binding proteins in human genetic disease

(2020) Fátima Gebauer et al.   NATURE REVIEWS GENETICS

RNA-Centric Methods: Toward the Interactome of Specific RNA Transcripts

(2020) Cathrin Gräwe et al.   TRENDS IN BIOTECHNOLOGY

A Comprehensive Survey on Graph Neural Networks

(2020) Zonghan Wu et al.   IEEE Transactions on Neural Networks and Learning Systems

Insight into novel RNA-binding activities via large-scale analysis of lncRNA-bound proteome and IDH1-bound transcriptome

(2019) Lichao Liu et al.   NUCLEIC ACIDS RESEARCH

From networks to optimal higher-order models of complex systems

(2019) Renaud Lambiotte et al.   Nature Physics

Methods to study RNA–protein interactions

(2019) Muthukumar Ramanathan et al.   NATURE METHODS

Challenges in measuring and understanding biological noise

(2019) Nils Eling et al.   NATURE REVIEWS GENETICS

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

(2019) Xiaoyong Pan et al.   Wiley Interdisciplinary Reviews-RNA

To Embed or Not: Network Embedding as a Paradigm in Computational Biology

(2019) Walter Nelson et al.   Frontiers in Genetics

Recent Advances in Machine Learning Based Prediction of RNA-protein Interactions

(2019) Amit Sagar et al.   PROTEIN AND PEPTIDE LETTERS

Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI

(2019) Alejandro Barredo Arrieta et al.   Information Fusion

Network structure from rich but noisy data

(2018) M. E. J. Newman   Nature Physics

A brave new world of RNA-binding proteins

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

A Survey of Methods for Explaining Black Box Models

(2018) Riccardo Guidotti et al.   ACM COMPUTING SURVEYS

Network enhancement as a general method to denoise weighted biological networks

(2018) Bo Wang et al.   Nature Communications

Peeking inside the black-box: A survey on Explainable Artificial Intelligence (XAI)

(2018) Amina Adadi et al.   IEEE Access

The Human RNA-Binding Proteome and Its Dynamics during Translational Arrest

(2018) Jakob Trendel et al.   CELL

Computational approaches for the analysis of RNA–protein interactions: A primer for biologists

(2018) Kat S. Moore et al.   JOURNAL OF BIOLOGICAL CHEMISTRY

CORUM: the comprehensive resource of mammalian protein complexes—2019

(2018) Madalina Giurgiu et al.   NUCLEIC ACIDS RESEARCH

Reconstructing Networks with Unknown and Heterogeneous Errors

(2018) Tiago P. Peixoto   Physical Review X

Computational analysis of CLIP-seq data

(2017) Michael Uhl et al.   METHODS

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

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

RNAcommender: genome-wide recommendation of RNA–protein interactions

(2016) Gianluca Corrado et al.   BIOINFORMATICS

Accurate prediction of RNA-binding protein residues with two discriminative structural descriptors

(2016) Meijian Sun et al.   BMC BIOINFORMATICS

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

(2016) Xiaoyong Pan et al.   BMC GENOMICS

Deep learning in bioinformatics

(2016) Seonwoo Min et al.   BRIEFINGS IN BIOINFORMATICS

SONAR Discovers RNA-Binding Proteins from Analysis of Large-Scale Protein-Protein Interactomes

(2016) Kristopher W. Brannan et al.   MOLECULAR CELL

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

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

Compact Integration of Multi-Network Topology for Functional Analysis of Genes

(2016) Hyunghoon Cho et al.   Cell Systems

A comprehensive comparative review of sequence-based predictors of DNA- and RNA-binding residues

(2015) Jing Yan et al.   BRIEFINGS IN BIOINFORMATICS

Three distinct ribosome assemblies modulated by translation are the building blocks of polysomes

(2015) Gabriella Viero et al.   JOURNAL OF CELL BIOLOGY

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

(2015) Babak Alipanahi et al.   NATURE BIOTECHNOLOGY

Specificity and nonspecificity in RNA–protein interactions

(2015) Eckhard Jankowsky et al.   NATURE REVIEWS MOLECULAR CELL BIOLOGY

ENCODE data at the ENCODE portal

(2015) Cricket A. Sloan et al.   NUCLEIC ACIDS RESEARCH

Evaluating link prediction methods

(2014) Yang Yang et al.   KNOWLEDGE AND INFORMATION SYSTEMS

Principles and Properties of Eukaryotic mRNPs

(2014) Sarah F. Mitchell et al.   MOLECULAR CELL

A census of human RNA-binding proteins

(2014) Stefanie Gerstberger et al.   NATURE REVIEWS GENETICS

GraphProt: modeling binding preferences of RNA-binding proteins

(2014) Daniel Maticzka et al.   GENOME BIOLOGY

Site identification in high-throughput RNA–protein interaction data

(2012) Philip J. Uren et al.   BIOINFORMATICS

Measuring reproducibility of high-throughput experiments

(2011) Qunhua Li et al.   Annals of Applied Statistics

Predicting RNA-Protein Interactions Using Only Sequence Information

(2011) Usha K Muppirala et al.   BMC BIOINFORMATICS

Interactome Networks and Human Disease

(2011) Marc Vidal et al.   CELL

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

(2010) Hilal Kazan et al.   PLoS Computational Biology

puma: a Bioconductor package for propagating uncertainty in microarray analysis

(2009) Richard D Pearson et al.   BMC BIOINFORMATICS

A Survey on Transfer Learning

(2009) Sinno Jialin Pan et al.   IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING

RNA processing and its regulation: global insights into biological networks

(2009) Donny D. Licatalosi et al.   NATURE REVIEWS GENETICS

Hypergraphs and Cellular Networks

(2009) Steffen Klamt et al.   PLoS Computational Biology

HITS-CLIP yields genome-wide insights into brain alternative RNA processing

(2008) Donny D. Licatalosi et al.   NATURE