Biologists say AI models like Evo 2 and AlphaGenome can't fully grasp the intricacies of gene regulation, which remains a mystery despite the Human Genome Project's 3 billion DNA sequence.
The human genome is less a script than a puzzle that gets harder the closer they look. Knowing the entire sequence has not helped much, as barely 2 percent of the human genome consists of actual genes.
Some are counting on outsourcing the analysis to artificial intelligence. Genomic 'foundation models' such as Evo 2, Genos, and Google DeepMind's AlphaGenome are trained on vast quantities of genomic data, which biologists use to make predictions about how differences in DNA sequence affect biological processes.
"Our genome is not what we might make it if we sat down at the drawing board," said Karen Adelman, a biologist who studies gene regulation at Harvard Medical School. Adelman noted that the traditional view posits that a small proportion of our DNA holds the code for making the protein molecules that orchestrate our cells' chemistry.
The deeper and much harder question is how those genes are used, or regulated, a question that seems to involve some and perhaps much of the rest of the genome. By switching suites of genes on and off, the many different cell types in our bodies can all be created from the same material.
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.
Source: wired
