Latest AI and machine learning research in genetics for healthcare professionals.
During DNA transcription, the central dogma states that DNA generates corresponding RNA sequences ba...
Purpose To develop and evaluate an automated system for extracting structured clinical information f...
Deep learning methods have played an increasingly pivotal role in advancing side-chain packing and m...
RNA torsion and pseudo-torsion angles are critical in determining the three-dimensional conformation...
Single-cell sequencing has advanced our understanding of cellular heterogeneity and disease patholog...
Recent advances in pharmacology are revolutionizing drug discovery and treatment strategies through ...
Most existing robot manipulation methods prioritize task learning by enhancing perception through ...
Mappings from biological sequences (DNA, RNA, protein) to quantitative measures of sequence functi...
We consider the problem of modelling the effects of unseen perturbations such as gene knockdowns o...
Summary: Long non-coding RNAs (lncRNAs) exert their functions by cooperating with other molecules ...
The subcellular localization of RNAs, including long non-coding RNAs (lncRNAs), messenger RNAs (mR...
BACKGROUND: mAm is a specific RNA modification that plays an important role in regulating mRNA stabi...
Single-cell RNA sequencing (scRNA-seq) enables high-resolution analysis of cellular heterogeneity,...
Advances in third-generation sequencing have enabled portable and real-time genomic sequencing, bu...
To overcome antimalarial drug resistance, carbohydrate derivatives as selective PfHT1 inhibitor ha...
Telomere-related genes (TRGs) are vital in diverse tumor types. Nevertheless, there is a notable lac...
BACKGROUND: Sepsis, a complex inflammatory condition with high mortality rates, lacks effective trea...
Recent advances in applying deep learning in genomics include DNA-language and single-cell foundat...
Background: Spatial transcriptomics have emerged as a powerful tool in biomedical research because...
Objective: This study investigates the potential of Large Language Models (LLMs) as an alternative...
Even though Deep Neural Networks are extremely powerful for image restoration tasks, they have sev...