A machine learning model developed by researchers at the Johns Hopkins Kimmel Cancer Center filters out the biological noise ...

New model extracts stiffness and fluidity from AFM data in minutes, enabling fast, accurate mechanical characterization of living cells at single-cell resolution. (Nanowerk Spotlight) Cells are not ...

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 classical drug discovery paradigm begins with a known molecular target: a protein whose modulation is expected to reverse ...

Researchers from several Parisian institutions have worked together to develop a non-destructive approach to study how unicellular organisms respond to stress, focusing on cell-to-cell differences.

STANFORD, California, USA, 24 June 2025 – In a comprehensive Genomic Press interview, Stanford University researcher Eric Sun reveals how machine learning is revolutionizing our understanding of brain ...

Brazilian researchers, in partnership with French institutions, have developed a tool that can predict how patients will respond to natalizumab, one of the most commonly used drugs for treating ...

To see structures within cells, scientists have to use labelling tools to tag the structures or proteins they’re investigating. While that is a precise method, there are many limitations; it only ...

With the rapid development of single-cell RNA sequencing (scRNA-seq), researchers can now examine gene activity in individual plant cells at unprecedented resolution, opening new opportunities to ...

Researchers at Korea University have developed a machine learning model for predicting sheet resistance in phosphorus oxychloride (POCl3) doping processes in solar cell manufacturing. “Our study aims ...