AIMC Topic: RNA

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PANTHER Score: Protein-Affinity for Nucleic Target-binding, Hybridization, and Energy Regression.

RNA (New York, N.Y.)
Although protein-RNA interactions are crucial for many biological processes, predicting their binding free energies (ΔG) is a challenging task due to limited available experimental data and the complexity of these interactions. To address this issue,...

Computational design of protein complexes: influence of binding affinity.

Chemical communications (Cambridge, England)
The interaction of proteins with diverse molecular partners, including other proteins, nucleic acids, and carbohydrates, is essential for performing various functions, from signal transduction and gene regulation to immune recognition and cellular tr...

Deep learning-assisted discovery of a potent and cell-active inhibitor of RNA N-methyladenosine recognition protein YTHDC2.

Nature communications
YTHDC2, a unique YTH-domain-containing protein that recognizes N6-methyladenosine (mA) on RNA, plays critical roles in diverse pathological processes and represents a promising therapeutic target. Despite its potential, no potent small-molecule inhib...

Proteome-wide computational analyses reveal links between protein condensate formation and RNA biology.

Science advances
Biomolecular condensates mediate dynamic compartmentalization of cellular processes. The multivalent interactions that underlie biomolecular condensation are often promoted by intrinsically disordered regions (IDRs) within proteins. Although the role...

Enhancing lipid nanoparticles-mediated RNA delivery to glioblastoma via targeted strategies.

Journal of controlled release : official journal of the Controlled Release Society
Glioblastoma (GBM) is an aggressive central nervous system (CNS) malignancy with a poor prognosis and limited responses to conventional therapies. RNA-based therapeutics, with their gene-targeting specificity, present a promising avenue for GBM treat...

MCLCBA: multi-view contrastive learning network for RNA methylation site prediction.

BMC bioinformatics
BACKGROUND: RNA methylation (RM) regulates gene expression regulation, RNA stability, and protein translation. Accurate prediction of RM modification sites is essential for understanding their biological functions. However, existing wet-lab detection...

Deep structural clustering reveals hidden systematic biases in RNA sequencing data.

Genome research
RNA sequencing (RNA-seq) is a pivotal tool for transcriptomic analysis, providing comprehensive exploration of gene expression across diverse biological contexts. However, RNA-seq data are susceptible to various biases that can significantly compromi...

A robust deep learning framework for RNA 5-methyluridine modification prediction using integrated features.

BMC biology
BACKGROUND: The discovery of RNA 5-methyluridine (m5U) modifications is vital in computational biology due to their essential significance in different biological processes. This study presents a powerful predictor named 5-meth-Uri, which improves th...

Advancing DNA and RNA Modification Detection via Nanopore Sequencing.

ACS nano
DNA/RNA modifications are crucial for biological processes. To understand their regulatory mechanisms, precise mapping and quantification of these modifications are essential. Although next-generation sequencing can detect the location and stoichiome...

Integrating AI and RNA biomarkers in cancer: advances in diagnostics and targeted therapies.

Cell communication and signaling : CCS
Early detection and personalized treatment strategies are essential for enhancing patient outcomes, as cancer continues to be a significant cause of mortality on a global basis. In clinical practice, the identification and validation of reliable biom...