AIMC Topic: RNA, Messenger

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rbpTransformer: A novel deep learning model for prediction of piRNA and mRNA bindings.

PloS one
An important issue in biotechnology is predicting whether a piRNA and an mRNA will or will not bind. Research and treatment of diseases, drug discovery, and the silencing and regulation of genes, transposons, and genomic stability may all benefit fro...

Artificial intelligence-driven discovery of novel scaffolds for selective TLR7 antagonists and their application in enhancing mRNA translation efficiency.

European journal of pharmaceutical sciences : official journal of the European Federation for Pharmaceutical Sciences
Toll-like receptor 7 (TLR7) is crucial in the innate immune response, responsible for recognizing single-stranded RNA from external pathogens and initiating the production of inflammatory cytokines and type I interferons. Despite the potential therap...

Identification of potential riboswitch elements in Homo sapiens mRNA 5'UTR sequences using positive-unlabeled machine learning.

PloS one
Riboswitches are a class of noncoding RNA structures that interact with target ligands to cause a conformational change that can then execute some regulatory purpose within the cell. Riboswitches are ubiquitous and well characterized in bacteria and ...

Deciphering disordered regions controlling mRNA decay in high-throughput.

Nature
Intrinsically disordered regions within proteins drive specific molecular functions despite lacking a defined structure. Although disordered regions are integral to controlling mRNA stability and translation, the mechanisms underlying these regulator...

Computational models for prediction of m6A sites using deep learning.

Methods (San Diego, Calif.)
RNA modifications play a crucial role in enhancing the structural and functional diversity of RNA molecules and regulating various stages of the RNA life cycle. Among these modifications, N6-Methyladenosine (m6A) is the most common internal modificat...

im7G-DCT: A two-branch strategy model based on improved DenseNet and transformer for m7G site prediction.

Computational biology and chemistry
N-7 methylguanosine (m7G) is an important RNA modification that plays a key role in regulating gene expression and cellular physiological functions. Medical research has shown that m7G is closely associated with the development of a variety of diseas...

Harnessing Computational Strategies to Overcome Challenges in mRNA Vaccines.

Physiology (Bethesda, Md.)
In recent years, the introduction of mRNA vaccines for SARS-CoV2 and respiratory syncytial virus (RSV) has highlighted the success of the mRNA technology platform. Designing mRNA sequences involves multiple components and requires balancing several p...

Identification of Biomarkers for Response to Interferon in Chronic Hepatitis B Based on Bioinformatics Analysis and Machine Learning.

Viral immunology
Interferon (IFN) is a pivotal agent against hepatitis B virus (HBV) in clinic, but there is a lack of accurate biomarkers to predict the response to IFN therapy in patients with chronic hepatitis B (CHB). Our study aimed to investigate potential targ...

Unveiling NLR pathway signatures: EP300 and CPN60 markers integrated with clinical data and machine learning for precision NASH diagnosis.

Cytokine
BACKGROUND: Given the increasing prevalence of metabolic dysfunction-associated fatty liver disease (MAFLD) and non-alcoholic steatohepatitis (NASH), there is a critical need for accurate non-invasive early diagnostic markers.

Deep learning to decode sites of RNA translation in normal and cancerous tissues.

Nature communications
The biological process of RNA translation is fundamental to cellular life and has wide-ranging implications for human disease. Accurate delineation of RNA translation variation represents a significant challenge due to the complexity of the process a...