Synthetic biology has been game-changing and with generative artificial intelligence, generative biology holds immense potential; let’s just speed it up.
Mirror-image nerve cells, tight bonds between neuron pairs and surprising axon swirls abound in a bit of gray matter smaller than a grain of rice.
Mann, J., Meshkin, H., Zirkle, J. et al. Mechanism-based organization of neural networks to emulate systems biology and pharmacology models. Sci Rep 14, 12,082 (2024). https://doi.org/10.1038/s41598-024-59378-9
One tool, called Find My Understudied Genes (FMUG), emerged from a study published in March1, which first explores why interesting, but relatively under-researched, genes are not highlighted in genetic surveys, and then offers FMUG as a remedy.
The second tool is the Unknome database, created by a team led by Matthew Freeman at the University of Oxford, UK, and Sean Munro at the MRC Laboratory of Molecular Biology, Cambridge, UK, that was described2 in 2023.
“We are in the lucky position to know what we don’t know,” says Thomas Stoeger, a biologist at Northwestern University in Chicago, Illinois, and co-author of the FMUG study.
Neuromorphic computing represents an exciting crossover between technology and biology, a frontier where computer science meets the mysteries of the human brain. Designed to mimic the way humans process information, this technology holds the promise to stir a revolution everywhere, from artificial intelligence to robotics. But what exactly is neuromorphic computing and why is it taking the center stage?
When you think of a criminal investigation, you might picture detectives meticulously collecting and analyzing evidence found at the scene: weapons, biological fluids, footprints and fingerprints. However, this is just the beginning of an attempt to reconstruct the events and individuals involved in the crime.
Life appears to require at least some instability. This fact should be considered a biological universality, proposes University of Southern California molecular biologist John Tower.
Biological laws are thought to be rare and describe patterns or organizing principles that appear to be generally ubiquitous. While they can be squishier than the absolutes of math or physics, such rules in biology nevertheless help us better understand the complex processes that govern life.
Most examples we’ve found so far seem to concern themselves with the conservation of materials or energy, and therefore life’s tendency towards stability.
While wearable technologies with embedded sensors, such as smartwatches, are widely available, these devices can be uncomfortable, obtrusive and can inhibit the skin’s intrinsic sensations.
“If you want to accurately sense anything on a biological surface like skin or a leaf, the interface between the device and the surface is vital,” said Professor Yan Yan Shery Huang from Cambridge’s Department of Engineering, who led the research. “We also want bioelectronics that are completely imperceptible to the user, so they don’t in any way interfere with how the user interacts with the world, and we want them to be sustainable and low waste.”
Alex Rosenberg is the R. Taylor Cole Professor of Philosophy at Duke University. His research focuses on the philosophy of biology and science more generally, mind, and economics.
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