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RNA, Messenger

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Transcorneal delivery of topically applied silver nanoparticles does not delay epithelial wound healing.

NanoImpact
Silver nanoparticles (AgNPs) are a common antimicrobial additive for a variety of applications, including wound care. However, AgNPs often undergo dissolution resulting in release of silver ions, with subsequent toxicity to mammalian cells. The corne...

Identification of biomarkers for acute leukemia via machine learning-based stemness index.

Gene
Traditional methods to understand leukemia stem cell (LSC)'s biological characteristics include constructing LSC-like cells and mouse models by transgenic or knock-in methods. However, there are some potential pitfalls in using this method, such as r...

The alterations of miRNA and mRNA expression profile and their integration analysis induced by silica nanoparticles in spermatocyte cells.

NanoImpact
Air pollution and the application of Silica nanoparticles (SiNPs) have increased the risk of human exposure to SiNPs. SiNPs are known to induce cytotoxicity in spermatocyte cells (GC-2spd cells) of mice and male reproductive system damage. However, t...

EDLmAPred: ensemble deep learning approach for mRNA mA site prediction.

BMC bioinformatics
BACKGROUND: As a common and abundant RNA methylation modification, N6-methyladenosine (mA) is widely spread in various species' transcriptomes, and it is closely related to the occurrence and development of various life processes and diseases. Thus, ...

Predicting mean ribosome load for 5'UTR of any length using deep learning.

PLoS computational biology
The 5' untranslated region plays a key role in regulating mRNA translation and consequently protein abundance. Therefore, accurate modeling of 5'UTR regulatory sequences shall provide insights into translational control mechanisms and help interpret ...

Full-length ribosome density prediction by a multi-input and multi-output model.

PLoS computational biology
Translation elongation is regulated by a series of complicated mechanisms in both prokaryotes and eukaryotes. Although recent advance in ribosome profiling techniques has enabled one to capture the genome-wide ribosome footprints along transcripts at...

Machine Learning Reduced Gene/Non-Coding RNA Features That Classify Schizophrenia Patients Accurately and Highlight Insightful Gene Clusters.

International journal of molecular sciences
RNA-seq has been a powerful method to detect the differentially expressed genes/long non-coding RNAs (lncRNAs) in schizophrenia (SCZ) patients; however, due to overfitting problems differentially expressed targets (DETs) cannot be used properly as bi...

Machine learning and bioinformatic analysis of brain and blood mRNA profiles in major depressive disorder: A case-control study.

American journal of medical genetics. Part B, Neuropsychiatric genetics : the official publication of the International Society of Psychiatric Genetics
This study analyzed gene expression messenger RNA data, from cases with major depressive disorder (MDD) and controls, using supervised machine learning (ML). We built on the methodology of prior studies to obtain more generalizable/reproducible resul...