AIMC Topic: RNA, Messenger

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Mechanism of liver X receptor α and ATP binding cassette transporter A1 involved in preeclampsia using an optimized deep learning model.

European review for medical and pharmacological sciences
OBJECTIVE: Preeclampsia (PE) is a complex disease-causing multisystem damage. Many genes, environmental factors, and their interactions are involved in the development and progression of PE. The pathogenesis of PE is not fully understood, limiting th...

Concepts and methods for transcriptome-wide prediction of chemical messenger RNA modifications with machine learning.

Briefings in bioinformatics
The expanding field of epitranscriptomics might rival the epigenome in the diversity of biological processes impacted. In recent years, the development of new high-throughput experimental and computational techniques has been a key driving force in d...

Revealing determinants of translation efficiency via whole-gene codon randomization and machine learning.

Nucleic acids research
It has been known for decades that codon usage contributes to translation efficiency and hence to protein production levels. However, its role in protein synthesis is still only partly understood. This lack of understanding hampers the design of synt...

An efficient deep learning based predictor for identifying miRNA-triggered phasiRNA loci in plant.

Mathematical biosciences and engineering : MBE
Phasic small interfering RNAs are plant secondary small interference RNAs that typically generated by the convergence of miRNAs and polyadenylated mRNAs. A growing number of studies have shown that miRNA-initiated phasiRNA plays crucial roles in regu...

Integrated mRNA sequence optimization using deep learning.

Briefings in bioinformatics
The coronavirus disease of 2019 pandemic has catalyzed the rapid development of mRNA vaccines, whereas, how to optimize the mRNA sequence of exogenous gene such as severe acute respiratory syndrome coronavirus 2 spike to fit human cells remains a cri...

RNAdegformer: accurate prediction of mRNA degradation at nucleotide resolution with deep learning.

Briefings in bioinformatics
Messenger RNA-based therapeutics have shown tremendous potential, as demonstrated by the rapid development of messenger RNA based vaccines for COVID-19. Nevertheless, distribution of mRNA vaccines worldwide has been hampered by mRNA's inherent therma...

EVlncRNA-Dpred: improved prediction of experimentally validated lncRNAs by deep learning.

Briefings in bioinformatics
Long non-coding RNAs (lncRNAs) played essential roles in nearly every biological process and disease. Many algorithms were developed to distinguish lncRNAs from mRNAs in transcriptomic data and facilitated discoveries of more than 600 000 of lncRNAs....

Geographic encoding of transcripts enabled high-accuracy and isoform-aware deep learning of RNA methylation.

Nucleic acids research
As the most pervasive epigenetic mark present on mRNA and lncRNA, N6-methyladenosine (m6A) RNA methylation regulates all stages of RNA life in various biological processes and disease mechanisms. Computational methods for deciphering RNA modification...

Adenosine Triphosphate Protects from Elevated Extracellular Calcium-Induced Damage in Human Proximal Kidney Cells: Using Deep Learning to Predict Cytotoxicity.

Cellular physiology and biochemistry : international journal of experimental cellular physiology, biochemistry, and pharmacology
BACKGROUND/AIMS: In kidney, extracellular [Ca] can modulate intracellular [Ca] to control key cellular processes. Hence, extracellular [Ca] is normally maintained within narrow range. We tested effect of extracellular ATP on viability of human proxim...

A novel ergodic cellular automaton gene network model towards efficient hardware-based genome simulator.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
In this paper, a novel ergodic cellular automaton model of Hes1 mRNA and Hes1 protein network is presented. Detailed analyses reveal that the presented network model can reproduce a typical nonlinear bifurcation phenomenon observed in a conventional ...