On knowing a gene: Distributional hypothesis of gene function Just as words derive meanings from context, genes can switch their roles with biological surroundings. Traditional gene annotations miss this Advances in transformers suggest a new perspective: gene functions as distributions over cellular contexts, similar to how words have context-dependent meanings cell.com/cell-systems/fullte… @CellSystemsCP Genes can exhibit pleiotropy, meaning they have multiple functions based on their biological context. Current ontologies often fail to capture this complexity Recent NLP breakthroughs, where word semantics are automatically learned from diverse contexts, offer a valuable analogy for understanding gene functions Modern distributional semantics uses vectors in a learned semantic space, driving innovations in LLMs and GPT models We outline a similar paradigm shift for gene functions. Viewing them as distributions over cellular contexts could empower models trained from extensive biological datasets @Harvard @HarvardDBMI @KempnerInst @harvard_data @DanaFarber @broadinstitute @GoogleDeepMind @joshbiology @JKwonBio @justguadaa W. Hahn