loading . . . Why the Human Genome’s Tangled Physicality May Confound AI | Quanta Magazine Bellissimo articolo su Quanta Magazine che vi invito a leggere sul perchè gli approcci di comprensione del genoma con AI non saranno sufficienti.
> the international Human Genome Project between 1990 and 2003 — hasn’t helped much. That investigation showed that barely 2% of the human genome consists of actual genes, the information-coding sequences of DNA.
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> This approach [Genomic “foundation models” such as Evo 2, Genos, and Google DeepMind’s AlphaGenome] is likely to be useful, but for those who crave real understanding of how the genome, and ultimately life itself, works, a computational black box will never suffice.
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> That’s because the genome is no blueprint or algorithm. It is something else.
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> The traditional view posits that a small proportion of our DNA holds the code for making the protein molecules that orchestrate our cells’ chemistry. Each instruction for a protein is held in a corresponding gene — we have around 20,000 of these — and gene sequences can range in length from a couple of dozen to almost 3 million DNA “letters” (representing molecules called nucleotides). Making a protein from its gene is a two-stage affair. First the DNA is read, letter by letter, by an enzyme called a polymerase, which creates a copy of that code in a related molecule called messenger RNA (mRNA). This is called transcription. The mRNA is then read by a piece of molecular machinery called the ribosome, which constructs the protein — a process called translation. The proteins made by the ribosome then go off to do their jobs in making and sustaining the organism.
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> This picture is still more or less correct. But it turns out that “the genes are probably not the most interesting part of the genome,” Adelman said.
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> How the genes that encode those proteins are regulated depends on some of the genome that doesn’t code for proteins.
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> Biologists have known about gene regulation, and the involvement of “noncoding” DNA, since the 1960s. But for many years, most of what they understood about this came from studies of simple organisms like bacteria, where the principles are generally straightforward. It has gradually become clear, though, that in complex eukaryotic organisms like us, gene regulation is far more complicated, involving overlapping systems of oversight and control, each with its own intricacies.
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> “It’s embarrassing that 25 years after the Human Genome Project, we don’t know where all the enhancers are in the genome, let alone what they do when they act and which genes they control,” said Wendy Bickmore (opens a new tab), a genome biologist at the University of Edinburgh.
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> Researchers developing AI-based genomic foundation models such as AlphaGenome hope that all these layers of regulation — transcription factors, splicing, epigenetic marks, loops, chromatin packing, and so on — will be implicitly included in the correlations that the algorithms learn between genetic sequence and organismal traits. …. But will that work?
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> “I’m sure [AlphaGenome] is going to be useful, but with limitations,” Bickmore said. “To me the big gap is in the complexity of the human body — in all the cell types and how they change over time in development. And all that data is missing.”
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> Fundamentally, the challenge is that the genome is not a set of static, linear instructions. It is highly dynamic, and it uses its information contextually, with combinatorial and promiscuous logic. “Whether we’ll ever be able to capture that aspect” in algorithms like AlphaGenome, “I don’t know,” she said.
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> So how should we think about the genome? Maybe the only metaphors that can capture the way the genome really works must come from biology itself. In 2020, the biological historian Evelyn Fox (opens a new tab) compared the genome to “an exquisitely sensitive reactive system.” Rather than a sequence of genes leading to the formation of traits, she said, it’s more of “a device for regulating the production of specific proteins in response to constantly changing signals it receives from its environment.”
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> “McClintock was far more on point than people realized at the time,” Adelman said. “What she said was that the genome isn’t static — it’s living.”
Source: _Why the Human Genome’s Tangled Physicality May Confound AI | Quanta Magazine_
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