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3D illustration of a DNA molecule with sparkling effects symbolizing complexity and genetic … More diversity. Futuristic concept of genomics, precision medicine, and computational life sciences.<\/p>\n
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If you\u2019ve been paying attention to modern research and AI, you know that genetics is a major application of this technology to our lives.<\/p>\n
Alphafold, for which its founders received a Nobel prize in science, is a major example, but it\u2019s just the tip of the iceberg when it comes to what AI is doing in healthcare, and in genetics in particular.<\/p>\n
This month we have a new announcement from the Chan Zuckerberg Initiative backed by Mark Zuckerberg and Melissa Chan that contemplates a brand new system called GREmLN (Gene Regulatory Embedding-based Large Neural model) for identifying cellular behavior.<\/p>\n
It may help with cancer research and work on other diseases.<\/p>\n
Part of the project involves an imaging technique, and assistance in developing software for scientists.<\/p>\n
There\u2019s also what CZ calls a \u201csingle cell data set\u201d of 1 billion cells, developed with 10X Genomics and Ultima Genomics. From reading documentation, it sounds like what this means is that teams assembled data on no less than a billion cells, in order to build a collective model of what an average cell would look like and how it would function.<\/p>\n
The new model, scientists suggest, can help to characterize genetic drivers of disease, and find new ways to restore diseased cells to health.<\/p>\n
Four Major Goals and Challenges<\/p>\n
Amongst the announcement of this ground-breaking resource, spokespersons at CZ identify four broader objectives scientists are reaching for:<\/p>\n
One involves building an AI-based virtual cell model \u2013 which GREmLN is presumably instrumental in.<\/p>\n
Another is \u201cdeveloping novel imaging technology to map, measure and model complex systems,\u201d which sounds like a similar type of exercise.<\/p>\n
Reportedly, the teams also hope to figure out how to directly sense inflammation in the body, and to harness the human immune system for various kinds of immunotherapy.<\/p>\n
Parsing these objectives further, you can see how the new GREmLN model will drive research on what the CZ Institute calls \u201cmolecular logic\u201d or the study of how parts of a cell interact or work together.<\/p>\n
What are Biohubs?<\/p>\n
A press release from Chan Zuckerberg also mentions the creation of Biohubs as laboratories fueling collaborative development, or, in the words of spokespersons, \u201ccross-disciplinary research institutions.\u201d<\/p>\n
ChatGPT provides a definition of a Biohub, and points out that the Chan Zuckerberg Biohubs are not the same as a series of Biohubs developed by the World Health Organization.<\/p>\n
\u201cBiohubs are collaborative research centers designed to accelerate breakthroughs in biomedical science by fostering interdisciplinary cooperation, sharing resources, and facilitating innovation,\u201d the model notes. \u201cTypically established through partnerships between universities, research institutions, healthcare providers, government agencies, and industry leaders, Biohubs aim to address complex biological and medical challenges by combining expertise across biology, medicine, engineering, computing, and data science. \u2026 Prominent examples include the Chan Zuckerberg Biohub, which unites Stanford, UCSF, and UC Berkeley researchers to tackle infectious diseases and advance biomedical knowledge through open science.\u201d<\/p>\n
Of the WHO Biohubs:<\/p>\n
\u201cA totally separate WHO initiative<\/strong> aimed at sharing biological materials<\/strong> (like virus samples with pandemic potential) among member states\u2026 So, while (CZ Biohubs and WHO Biohubs) share the \u2018Biohub\u2019 name, their missions, governance, and affiliations are entirely distinct.\u201d<\/p>\n The concept, however, is the same \u2013 scientists are banding together to do more innovative work on cell structure, for example, in nucleus and mitochondria DNA.<\/p>\n A little research shows some of the distinctions between different types of DNA present in a cell.<\/p>\n A lot of the DNA is isolated in the nucleus of the cell, but there\u2019s also mitochondria, less attached to that central cluster.<\/p>\n Literature Weighs In<\/p>\n Fans of Madeleine L\u2019Engle\u2019s youth fiction in the 1980s will note that her work explored the idea of subcellular entities and their impact on macroscopic systems.<\/p>\n Just for fun. I ask ChatGPT about L\u2019Engle\u2019s impact on modern cellular and genomic research.<\/p>\n \u201cMadeleine L’Engle\u2019s work didn’t explicitly prefigure specific contemporary research into genetics or mitochondria, but her writing, particularly A Wrinkle in Time (1962), A Wind in the Door (1973), and the rest of her Time Quintet, did anticipate broad scientific and philosophical themes related to cellular biology, mitochondrial function, interconnectedness, and universal harmony,\u201d the model said. \u201cIn A Wind in the Door, for instance, L’Engle explores the concept of \u2018farandolae,\u2019 fictional microscopic entities within mitochondria, whose harmony or disharmony directly affects the health of living organisms and even the universe. Her vision captured a holistic view of biology, recognizing mitochondria as fundamental life engines, long before mainstream science widely emphasized mitochondria\u2019s central role in health, aging, and diseases.\u201d<\/p>\n How many readers remember the farandolae, which L\u2019Engle characterized in promoting a kind of social symbiosis that was a more prominent idea in a less data-driven age?<\/p>\n