Machine learning is a powerful tool in computational biology, enabling the analysis of a wide range of biomedical data such as genomic sequences and biological imaging. But when researchers use ...

Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered ...

The progress of machine learning over the past decade, driven by the advent of deep learning, has been remarkable. And systems biology, which seeks to understand the big picture by collecting large ...

The rapidly expanding field of machine learning is driving significant innovations across various industries, with profound implications for healthcare and biological research. The upcoming Special ...

In the last several years, large language models (LLMs) like ChatGPT and Bard have shown the world the astounding power of generative AI for language creation tools. However, some of the most exciting ...

On Sunday, April 14, students participating in Cornell’s Microbiome Hackathon wrapped up 28 hours of work by showing off their creations which included an app to predict one’s risk of neurological ...

In fields such as biotechnology, medicine, pharmaceutical, health care, and life sciences, the need to ensure human health and safety is of the highest priority when deploying artificial intelligence ...

In an interview with Technology Networks, Dr. Daniel Reker discusses how machine learning is improving data-scarce areas of drug discovery.

Cell culture is a foundational technology widely used across fields such as pharmaceutical production, regenerative medicine, food science, and materials engineering. A critical component of ...

The Kushal Dey lab in the Computational and Systems Biology program at the Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, has 1 postdoctoral fellow position available in ...