University of Virginia School of Medicine scientists have identified a widespread source of error in a popular method for ...
Machine learning (ML) has emerged as a transformative approach for decoding the genomic determinants of antimicrobial resistance (AMR). By leveraging large-scale sequencing data, ML models can discern ...
Early detection of lung cancer in smokers using miRNA profiles and a hybrid deep learning framework. This is an ASCO Meeting Abstract from the 2025 ASCO Annual Meeting I. This abstract does not ...
In a comprehensive Genomic Press interview, Stanford University researcher Eric Sun reveals how machine learning is revolutionizing our understanding of brain aging at an unprecedented cellular ...
A diagram outlining the experimental workflow for the UVA team's investigation of transcribed ultra conserved regions (TUCRs) in glioblastoma. Glioblastoma is an extremely aggressive type of brain ...
The accelerating capability of technology is releasing vast quantities of genomic data. This promises powerful benefits for personal and population health. Harnessing this power will depend on public ...
Artificial intelligence is moving from the margins of virology into its operational core. It can scan viral genomes, ...
In the face of climate change, apple breeding programs need innovative ways to select cultivars that can thrive under diverse conditions. A recent study demonstrates how integrating genomic data with ...
The field of livestock genomics has experienced remarkable progress over the past two decades, ushering in a new era of data-driven breeding practices.
The data science and machine learning technology space is undergoing rapid changes, fueled primarily by the wave of generative AI and—just in the last year—agentic AI systems and the large language ...
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