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RNA-Binding Proteins

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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...

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...

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...

Artificial intelligence-assisted RNA-binding protein signature for prognostic stratification and therapeutic guidance in breast cancer.

Frontiers in immunology
BACKGROUND: Breast cancer is the most common malignancy in women globally, with significant heterogeneity affecting prognosis and treatment. RNA-binding proteins play vital roles in tumor progression, yet their prognostic potential remains unclear. T...

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...

Structure-Based Prediction of lncRNA-Protein Interactions by Deep Learning.

Methods in molecular biology (Clifton, N.J.)
The interactions between long noncoding RNA (lncRNA) and protein play crucial roles in various biological processes. Computational methods are essential for predicting lncRNA-protein interactions and deciphering their mechanisms. In this chapter, we ...

Key RNA-binding proteins in renal fibrosis: a comprehensive bioinformatics and machine learning framework for diagnostic and therapeutic insights.

Renal failure
BACKGROUND: Renal fibrosis is a critical factor in chronic kidney disease progression, with limited diagnostic and therapeutic options. Emerging evidence suggests RNA-binding proteins (RBPs) are pivotal in regulating cellular mechanisms underlying fi...

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...

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.

ASiDentify (ASiD): a machine learning model to predict new autism spectrum disorder risk genes.

Genetics
Autism spectrum disorder (ASD) is a neurodevelopmental disorder that affects nearly 3% of children and has a strong genetic component. While hundreds of ASD risk genes have been identified through sequencing studies, the genetic heterogeneity of ASD ...