Fluorescent dyes have long been used in biological research to identify and visualize structures within living cells. Although effective, they have several drawbacks, including altering the cells under study, limiting the number of structures that can be examined at once and reducing measurement accuracy.

A team led by University at Buffalo researchers has developed a new method that draws on advances in artificial intelligence and Raman spectroscopy to overcome the limitations of dye-based imaging.

The approach combines AI with “Ramanomics,” a UB-pioneered optical technology that measures the biochemical makeup of cells without altering them. Rather than relying on fluorescent labels, which are dyes that bind to specific cellular components and glow under specialized lighting, it identifies cellular structures by their unique biochemical signatures.