Latest AI and machine learning research in genetics for healthcare professionals.
In India, newborn screening (NBS) is essential for detecting health problems in infants. Despite sig...
OBJECTIVE: Artificial intelligence (AI) holds enormous potential for noninvasively identifying patie...
INTRODUCTION: Accumulating evidence demonstrates that aberrant methylation of enhancers is crucial i...
RNA nanotechnology aims to use RNA as a programmable material to create self-assembling nanodevices ...
Proteins are used in various biotechnological applications, often requiring the optimization of prot...
Protein missense mutations and resulting protein stability changes are important causes for many hum...
Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) could ai...
Protein-DNA and protein-RNA interactions are involved in many biological processes and regulate many...
This study aimed to develop a deep learning (DL) model for predicting the recurrence risk of lung ad...
Deep convolutional neural networks have shown advanced performance in accurately segmenting images. ...
Stochastic and robust optimization approaches often result in sub-optimal solutions for the uncertai...
Unlike proteins, which have a wealth of validated structural data, experimentally or computationally...
Continuous effluent quality prediction in wastewater treatment processes is crucial to proactively r...
The specific genetic subtypes that gliomas exhibit result in variable clinical courses and the need ...
Using the CRISPR-Cas9 system to perform base substitutions at the target site is a typical technique...
Ovarian cancer (OC), known for its pronounced heterogeneity, has long evaded a unified classificatio...
Epithelial ion and fluid transport studies in patient-derived organoids (PDOs) are increasingly bein...
N6-methyladenosine (m6A) is the most prevalent, abundant, and conserved internal modification in the...
Clinicopathological presentations are critical for establishing a postoperative treatment regimen in...
Source attribution has traditionally involved combining epidemiological data with different pathogen...
To explore a robust tool for advancing digital breeding practices through an artificial intelligence...