Genetic testing is becoming an increasingly important component of reproductive health care. It has evolved, over the years, ...

Key opportunities in the AI in genomics market include the increasing adoption of precision medicine, AI-driven genome ...

University of Pittsburgh postdoctoral researcher Mary Cundiff uses machine learning and single-cell genomics to study ...

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 ...

Artificial intelligence (AI) machine learning is rapidly emerging as a powerful tool in the quest for novel diagnostics, therapies, and treatment for complex diseases such as cancer. Increasingly, ...

Funding will expand the range of Dualase® genome editors for new high morbidity and mortality genetic disease targets. TORONTO, March 18, 2026 /PRNewswire/ - Specific Biologics Inc. ("Specific"), a ...

You're currently following this author! Want to unfollow? Unsubscribe via the link in your email. Last week, a group of Amazon scientists and engineers gathered to dream big. The event was all about ...

AI in high-throughput screening is reshaping how large-scale experimental datasets are processed, interpreted and translated into actionable biological insights. As screening campaigns routinely ...

Augmented curation of disease diagnoses and medications for patients with hepatocellular carcinoma. Exchanging genomics reports between pathology labs and medical centers using the Minimal Clinical ...

Antimicrobial resistance (AMR) is considered one of the most urgent global public health threats, with experts predicting that AMR could cause 39 million deaths between 2025 and 2050. AMR is not a ...