Chinese AI Reveals Hidden Protein Links in Distant Species
A Chinese research team used AI to find protein links across very different species. They focused on traits like echolocation found in bats and whales. The AI model looked deeper than simple sequence matching.
They detected patterns in protein structure that standard methods miss. Therefore, they showed how convergence at protein level works. The study explains how unrelated animals evolve similar functions.
They call their computational tool ACEP. It uses a pre-trained protein language model to compare deep structural features. In addition, it can spot hidden similarities that seem unrelated at first glance.
Why This Discovery Matters
This finding changes how we see evolution. It suggests that molecular details play a greater role than thought. For example, traits can meet via hidden protein features rather than obvious gene matches.
It also empowers biologists to link traits across life forms. They can now look beyond obvious similarities. As a result, scientists may better understand evolutionary convergence.
Moreover, this work shows AI’s growing value in biology. The team combined AI with protein analysis to decode complex signals. Future research can use this approach to study other convergent traits.
This study also raises new questions. What other traits hide beneath surface differences? Can we apply this method across many species? The answers will deepen our understanding of life’s diversity.=-/*9
