Changes in chromatin state upstream, for example, can shape gene expression downstream—and models have long recognized those links. Gerstein said AlphaGenome stands out because it tries to predict multiple genomic signals simultaneously and treats them as connected rather than independent. AlphaGenome distinguishes itself from earlier genomic models by learning from multiple types of biological measurements simultaneously.
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