AI analyzes cell movements under the microscope Houssenia Writing

AI analyzes cell movements under the microscope – Houssenia Writing

The enormous amount of data that can be obtained by filming biological processes with a microscope has so far been an obstacle to analysis. Thanks to artificial intelligence (AI), researchers at the University of Gothenburg can now track the movement of cells in time and space. The method could be very useful in developing more effective cancer drugs.

Studying the movements and behavior of cells and biological molecules under the microscope provides fundamental information to better understand the processes related to our health. Studies of cell behavior in different scenarios are important for the development of new medical technologies and treatments.

“In the last two decades, optical microscopy has evolved significantly. It allows us to study biological life in great detail, both spatially and temporally. Living systems move in all possible directions and at different speeds,” explains Jesús Pineda, PhD student. at the University of Gothenburg and first author of the scientific article in Natural Machine Intelligence.

Mathematics describes the relationships between the particles

Advances have provided researchers with such large amounts of data today that analysis is almost impossible. But now researchers at the University of Gothenburg have developed an AI method that combines graph theory and neural networks and can select reliable information from video clips.

Graph theory is a mathematical structure used to describe the relationships between different particles in the sample under study. It is comparable to a social network in which particles interact and directly or indirectly influence the behavior of others.

“The AI ​​method uses the graph information to adapt to different situations and can solve multiple tasks in different experiments. For example, our AI can reconstruct the path that individual cells or molecules take to fulfill a specific biological function. This means researchers can test the effectiveness of different drugs and see how well they work as a potential cancer treatment,” says Jesús Pineda.

Pharmaceutical companies are already using AI

AI also makes it possible to describe all dynamic aspects of particles in situations where other methods would not be effective. For this reason, pharmaceutical companies have already included this method in their research and development process.

Facts: Neural Networks Neural networks learn to gather the specific information a researcher is looking for from an image using self-supervised learning. The tool simplifies the analysis process and allows collecting large amounts of detailed information from the data-rich videos.