The immense amount of data acquired by filming biological processes with the help of a microscope has been a hindrance for analyses. Utilizing artificial intelligence (AI), it is now possible for scientists at the University of Gothenburg to track cell movement through space and time.
Jesús Pineda. Image Credit: Malin Arnesson.
This technique could be highly beneficial for developing more efficient cancer medications.
Basic information for gaining better insight into the processes pertaining to health has been offered by learning the movements and behaviors of biological molecules and cells under a microscope. Studies of how cells tend to act in various scenarios are significant factors for coming up with new medical technologies and treatments.
In the past two decades, optical microscopy has advanced significantly. It enables us to study biological life down to the smallest detail in both space and time. Living systems move in every possible direction and at different speeds" said Jesús Pineda, first author and doctoral student at the University of Gothenburg
Pineda published the scientific article in the journal Nature Machine Intelligence.
Math Describes Relationships of Particles
The newly-made developments have provided researchers with such huge amounts of data that analysis is almost impossible. However, researchers at the University of Gothenburg have come up with an AI technique integrating neural networks and graph theory that has the potential to select trustworthy information from video clips.
Graph theory is a mathematical structure that has been utilized to explain the relationships between different particles in the sample that has been studied. It is equivalent to a social network in which the particles interact and impact one another’s behavior in a direct or indirect manner.
The AI method uses the information in the graph to adapt to different situations and can solve multiple tasks in different experiments.
Jesús Pineda, Study First Author and Doctoral Student, University of Gothenburg
Pineda added, “For example, our AI can reconstruct the path that individual cells or molecules take when moving to achieve a certain biological function. This means that researchers can test the effectiveness of different medications and see how well they work as potential cancer treatments.”
Pharmaceutical Companies Already Using AI
Furthermore, AI makes it feasible to explain all dynamic views of particles in situations where other techniques would not be efficient. For this reason, pharmaceutical companies have integrated this method into their research and development processes.
Journal Reference
Pineda, J., et al. (2023) Geometric deep learning reveals the spatiotemporal features of microscopic motion. Nature Machine Intelligence. doi.org/10.1038/s42256-022-00595-0.