AIMC Topic: RNA-Binding Proteins

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RBPsuite 2.0: an updated RNA-protein binding site prediction suite with high coverage on species and proteins based on deep learning.

BMC biology
BACKGROUND: RNA-binding proteins (RBPs) play crucial roles in many biological processes, and computationally identifying RNA-RBP interactions provides insights into the biological mechanism of diseases associated with RBPs.

RNA-protein interaction prediction using network-guided deep learning.

Communications biology
Accurate computational determination of RNA-protein interactions remains challenging, particularly when encountering unknown RNAs and proteins. The limited number of RNAs and their flexibility constrained the effectiveness of the deep-learning models...

ZeRPI: A graph neural network model for zero-shot prediction of RNA-protein interactions.

Methods (San Diego, Calif.)
RNA-protein interactions are crucial for biological functions across multiple levels. RNA binding proteins (RBPs) intricately engage in diverse biological processes through specific RNA molecule interactions. Previous studies have revealed the indisp...

Assessing donor kidney function: the role of CIRBP in predicting delayed graft function post-transplant.

Frontiers in immunology
INTRODUCTION: Delayed graft function (DGF) shortens the survival time of transplanted kidneys and increases the risk of rejection. Current methods are inadequate in predicting DGF. More precise tools are required to assess kidney suitability for tran...

DeepMiRBP: a hybrid model for predicting microRNA-protein interactions based on transfer learning and cosine similarity.

BMC bioinformatics
BACKGROUND: Interactions between microRNAs and RNA-binding proteins are crucial for microRNA-mediated gene regulation and sorting. Despite their significance, the molecular mechanisms governing these interactions remain underexplored, apart from sequ...

AGML: Adaptive Graph-Based Multi-Label Learning for Prediction of RBP and as Event Associations During EMT.

IEEE/ACM transactions on computational biology and bioinformatics
Increasing evidence has indicated that RNA-binding proteins (RBPs) play an essential role in mediating alternative splicing (AS) events during epithelial-mesenchymal transition (EMT). However, due to the substantial cost and complexity of biological ...

An Integrated TCN-CrossMHA Model for Predicting circRNA-RBP Binding Sites.

Interdisciplinary sciences, computational life sciences
Circular RNA (circRNA) has the capacity to bind with RNA binding protein (RBP), thereby exerting a substantial impact on diseases. Predicting binding sites aids in comprehending the interaction mechanism, thereby offering insights for disease treatme...

Data-augmented machine learning scoring functions for virtual screening of YTHDF1 mA reader protein.

Computers in biology and medicine
Machine learning is rapidly advancing the drug discovery process, significantly enhancing speed and efficiency. Innovation in computer-aided drug design is primarily driven by structure- and ligand-based approaches. When the number of known inhibitor...

Rapid detection of mouse spermatogenic defects by testicular cellular composition analysis via enhanced deep learning model.

Andrology
BACKGROUND: Histological analysis of the testicular sections is paramount in infertility research but tedious and often requires months of training and practice.

Capture of RNA-binding proteins across mouse tissues using HARD-AP.

Nature communications
RNA-binding proteins (RBPs) modulate all aspects of RNA metabolism, but a comprehensive picture of RBP expression across tissues is lacking. Here, we describe our development of the method we call HARD-AP that robustly retrieves RBPs and tightly asso...