GenBank

Carbon-A, a DNA annotation model, has been used to identify 566 million previously unlogged gene candidates, with the work documented in a new technical write-up covering genome annotation at GenBank scale. The result suggests large-scale machine learning can flag vast numbers of potential genes that standard pipelines missed. Discussion is centered on how reliable these candidates are and what validating them at such volume would require.