Revealing protein–lncRNA interaction
F Ferre, A Colantoni… - Briefings in …, 2016 - academic.oup.com
Long non-coding RNAs (lncRNAs) are associated to a plethora of cellular functions, most of
which require the interaction with one or more RNA-binding proteins (RBPs); similarly, RBPs …
which require the interaction with one or more RNA-binding proteins (RBPs); similarly, RBPs …
Protein–RNA interaction prediction with deep learning: structure matters
Protein–RNA interactions are of vital importance to a variety of cellular activities. Both
experimental and computational techniques have been developed to study the interactions …
experimental and computational techniques have been developed to study the interactions …
Predicting the sequence specificities of DNA-and RNA-binding proteins by deep learning
Knowing the sequence specificities of DNA-and RNA-binding proteins is essential for
developing models of the regulatory processes in biological systems and for identifying …
developing models of the regulatory processes in biological systems and for identifying …
Prediction of RNA-protein sequence and structure binding preferences using deep convolutional and recurrent neural networks
Background RNA regulation is significantly dependent on its binding protein partner, known
as the RNA-binding proteins (RBPs). Unfortunately, the binding preferences for most RBPs …
as the RNA-binding proteins (RBPs). Unfortunately, the binding preferences for most RBPs …
A deep learning framework for modeling structural features of RNA-binding protein targets
RNA-binding proteins (RBPs) play important roles in the post-transcriptional control of
RNAs. Identifying RBP binding sites and characterizing RBP binding preferences are key …
RNAs. Identifying RBP binding sites and characterizing RBP binding preferences are key …
Integrative regulatory mapping indicates that the RNA-binding protein HuR couples pre-mRNA processing and mRNA stability
RNA-binding proteins coordinate the fates of multiple RNAs, but the principles underlying
these global interactions remain poorly understood. We elucidated regulatory mechanisms …
these global interactions remain poorly understood. We elucidated regulatory mechanisms …
Predicting RNA–protein binding sites and motifs through combining local and global deep convolutional neural networks
X Pan, HB Shen - Bioinformatics, 2018 - academic.oup.com
Motivation RNA-binding proteins (RBPs) take over 5–10% of the eukaryotic proteome and
play key roles in many biological processes, eg gene regulation. Experimental detection of …
play key roles in many biological processes, eg gene regulation. Experimental detection of …
An oxygen-regulated switch in the protein synthesis machinery
J Uniacke, CE Holterman, G Lachance, A Franovic… - Nature, 2012 - nature.com
Protein synthesis involves the translation of ribonucleic acid information into proteins, the
building blocks of life. The initial step of protein synthesis is the binding of the eukaryotic …
building blocks of life. The initial step of protein synthesis is the binding of the eukaryotic …
Comprehensive evaluation of deep learning architectures for prediction of DNA/RNA sequence binding specificities
Motivation Deep learning architectures have recently demonstrated their power in predicting
DNA-and RNA-binding specificity. Existing methods fall into three classes: Some are based …
DNA-and RNA-binding specificity. Existing methods fall into three classes: Some are based …
POSTAR2: deciphering the post-transcriptional regulatory logics
Post-transcriptional regulation of RNAs is critical to the diverse range of cellular processes.
The volume of functional genomic data focusing on post-transcriptional regulation logics …
The volume of functional genomic data focusing on post-transcriptional regulation logics …