AI Medical Compendium Topic

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ScoMorphoFISH: A deep learning enabled toolbox for single-cell single-mRNA quantification and correlative (ultra-)morphometry.

Journal of cellular and molecular medicine
Increasing the information depth of single kidney biopsies can improve diagnostic precision, personalized medicine and accelerate basic kidney research. Until now, information on mRNA abundance and morphologic analysis has been obtained from differen...

DeepTESR: A Deep Learning Framework to Predict the Degree of Translational Elongation Short Ramp for Gene Expression Control.

ACS synthetic biology
Controlling translational elongation is essential for efficient protein synthesis. Ribosome profiling has revealed that the speed of ribosome movement is correlated with translational efficiency in the translational elongation ramp. In this work, we ...

Inferring protein expression changes from mRNA in Alzheimer's dementia using deep neural networks.

Nature communications
Identifying the molecular systems and proteins that modify the progression of Alzheimer's disease and related dementias (ADRD) is central to drug target selection. However, discordance between mRNA and protein abundance, and the scarcity of proteomic...

Therapeutic enzyme engineering using a generative neural network.

Scientific reports
Enhancing the potency of mRNA therapeutics is an important objective for treating rare diseases, since it may enable lower and less-frequent dosing. Enzyme engineering can increase potency of mRNA therapeutics by improving the expression, half-life, ...

sRNARFTarget: a fast machine-learning-based approach for transcriptome-wide sRNA target prediction.

RNA biology
Bacterial small regulatory RNAs (sRNAs) are key regulators of gene expression in many processes related to adaptive responses. A multitude of sRNAs have been identified in many bacterial species; however, their function has yet to be elucidated. A ke...

A novel strategy to uncover specific GO terms/phosphorylation pathways in phosphoproteomic data in Arabidopsis thaliana.

BMC plant biology
BACKGROUND: Proteins are the workforce of the cell and their phosphorylation status tailors specific responses efficiently. One of the main challenges of phosphoproteomic approaches is to deconvolute biological processes that specifically respond to ...

Biological features between miRNAs and their targets are unveiled from deep learning models.

Scientific reports
MicroRNAs (miRNAs) are ~ 22 nucleotide ubiquitous gene regulators. They modulate a broad range of essential cellular processes linked to human health and diseases. Consequently, identifying miRNA targets and understanding how they function are critic...

Novel deep learning-based solution for identification of prognostic subgroups in liver cancer (Hepatocellular carcinoma).

BMC bioinformatics
BACKGROUND: Liver cancer (Hepatocellular carcinoma; HCC) prevalence is increasing and with poor clinical outcome expected it means greater understanding of HCC aetiology is urgently required. This study explored a deep learning solution to detect bio...

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...