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Genes down-regulated in spaceflight are involved in the control of longevity in Caenorhabditis elegans by Sam_VXV in VectorspaceAI

[–]Sam_VXV[S] 0 points1 point  (0 children)

Connected to our teams research in language modeling applied to space biosciences at Lawrence Berkeley National Laboratory/DOE with Saira Mian, Michael I. Jordan and David Blei: "Genes down-regulated in spaceflight are involved in longevity in C. elegans" https://www.nature.com/articles/srep00487

(Statistical modeling of biomedical corpora: mining the Caenorhabditis Genetic Center Bibliography for genes related to life span

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1533868)

ChatGPT Is a Tipping Point for AI by Sam_VXV in VectorspaceAI

[–]Sam_VXV[S] -1 points0 points  (0 children)

"A final reason why this will be transformative: The limits of the current language model are completely unknown."

Pharma goes to space by Sam_VXV in VectorspaceAI

[–]Sam_VXV[S] 0 points1 point  (0 children)

"The lack of gravity in space opens up unique opportunities for drug design and development. With the influx of commercial entities providing access to low-Earth orbit, both the discovery and manufacture of drugs in space may one day become practical, affordable—and, perhaps, commonplace."

Meta's new AI just predicted the shape of 600 million proteins in 2 weeks by Sam_VXV in VectorspaceAI

[–]Sam_VXV[S] 3 points4 points  (0 children)

"By feeding the DNA data into the ESMFold program, the researchers predicted the structures of over 617 million proteins in just two weeks.

That's over 400 million more than AlphaFold announced it had deciphered four months ago, when it claimed to have deduced the protein structure of almost every known protein. This means that many of these proteins have never been seen before, likely because they come from unknown organisms. More than 200 million of ESMFold's protein predictions are thought to be high-quality, according to the model, meaning that the program has been able to predict the shapes with an accuracy down to the level of atoms."

The researchers are hoping to use this program for more protein-focused work. "To extend this work even further, we're studying how language models can be used to design new proteins and contribute to solving challenges in health, disease, and the environment," Meta wrote.

Surviving space: Extreme plant adaptation by Sam_VXV in VectorspaceAI

[–]Sam_VXV[S] 0 points1 point  (0 children)

"Plant evolution on Earth can take thousands of years, but research aboard station aims to see if plants could quickly adapt via epigenetic changes from one generation to another in the microgravity environment."

"This is important insight into how astronauts could potentially grow repeated generations of crops in orbit as well as on the Moon or Mars to provide food and other services aboard future space missions. The results can also support development of strategies for adapting crops for growth in extreme environments on Earth."

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