Genetics

DNA Origami Nanostructure Detection and Yield Estimation Using Deep Learning.

DNA origami is a milestone in DNA nanotechnology. It is robust and efficient in constructing arbitrary two- and three-dimensional nanostructures. The shape and size of origami structures vary. To characterize them, an atomic force microscope, a transmission electron microscope, and other microscopes are utilized. However, the identification of various origami nanostructures heavily depends on the ...

Deep Learning for Noninvasive Assessment of H3 K27M Mutation Status in Diffuse Midline Gliomas Using MR Imaging.

BACKGROUND: Determination of H3 K27M mutation in diffuse midline glioma (DMG) is key for prognostic assessment and stratifying patient subgroups for clinical trials. MRI can noninvasively depict morphological and metabolic characteristics of H3 K27M mutant DMG.

Deep learning identified genetic variants for COVID-19-related mortality among 28,097 affected cases in UK Biobank.

Analysis of host genetic components provides insights into the susceptibility and response to viral infection such as severe acute respiratory syndrom...

Recognizing the power of machine learning and other computational methods to accelerate progress in small molecule targeting of RNA.

RNA structures regulate a wide range of processes in biology and disease, yet small molecule chemical probes or drugs that can modulate these function...

A robust and lightweight deep attention multiple instance learning algorithm for predicting genetic alterations.

Self-attention mechanism-based algorithms are attractive in digital pathology due to their interpretability, but suffer from computation complexity. T...

Major evolutionary transitions in individuality between humans and AI.

That humans might undergo future evolutionary transitions in individuality (ETIs) seems fanciful. However, drawing upon recent thinking concerning the...

Comparison of the Diagnostic Performance of Deep Learning Algorithms for Reducing the Time Required for COVID-19 RT-PCR Testing.

(1) Background: Rapid and accurate negative discrimination enables efficient management of scarce isolated bed resources and adequate patient accommod...

Editorial for "Deep Learning for Noninvasive Assessment of H3 K27M Mutation Status in Diffuse Midline Gliomas Using MR Imaging".

Prediction of pathologic complete response to neoadjuvant systemic therapy in triple negative breast cancer using deep learning on multiparametric MRI.

Triple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer. Neoadjuvant systemic therapy (NAST) followed by surgery are currently ...

A radiomics-based deep learning approach to predict progression free-survival after tyrosine kinase inhibitor therapy in non-small cell lung cancer.

BACKGROUND: The epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs) are a first-line therapy for non-small cell lung cancer (NSC...

Multienzyme deep learning models improve peptide de novo sequencing by mass spectrometry proteomics.

Generating and analyzing overlapping peptides through multienzymatic digestion is an efficient procedure for de novo protein using from bottom-up mass...

Smart de novo Macromolecular Structure Modeling from Cryo-EM Maps.

The study of macromolecular structures has expanded our understanding of the amazing cell machinery and such knowledge has changed how the pharmaceuti...

Drone-assisted collection of environmental DNA from tree branches for biodiversity monitoring.

The protection and restoration of the biosphere is crucial for human resilience and well-being, but the scarcity of data on the status and distributio...

MultiScale-CNN-4mCPred: a multi-scale CNN and adaptive embedding-based method for mouse genome DNA N4-methylcytosine prediction.

N4-methylcytosine (4mC) is an important epigenetic mechanism, which regulates many cellular processes such as cell differentiation and gene expression...

Energy consumption prediction using the GRU-MMattention-LightGBM model with features of Prophet decomposition.

The prediction of energy consumption is of great significance to the stability of the regional energy supply. In previous research on energy consumpti...

Predicting prime editing efficiency and product purity by deep learning.

Prime editing is a versatile genome editing tool but requires experimental optimization of the prime editing guide RNA (pegRNA) to achieve high editin...

Performance of the Vitek 2 Advanced Expert System (AES) as a Rapid Tool for Reporting Antimicrobial Susceptibility Testing (AST) in from North and Latin America.

This study evaluated the performance of the Vitek 2 Advanced Expert System (AES) confidence level report as a rapid tool for reporting antimicrobial s...

A deep learning based method for automatic analysis of high-throughput droplet digital PCR images.

Droplet digital PCR (ddPCR) is a technique for absolute quantification of nucleic acid molecules and is widely used in biomedical research and clinica...

Optimizing variant-specific therapeutic SARS-CoV-2 decoys using deep-learning-guided molecular dynamics simulations.

Treatment of COVID-19 with a soluble version of ACE2 that binds to SARS-CoV-2 virions before they enter host cells is a promising approach, however it...

Automated warfarin dose prediction for Asian, American, and Caucasian populations using a deep neural network.

Existing warfarin dose prediction algorithms based on pharmacogenetics and clinical parameters have not been used clinically due to the absence of ext...