Mohamed Mokhtar Elshrif

MELD puts the score difference between wild-type and mutant sequence directly into the supervised objective, instead of training on absolute signal and comparing two sequences after the fact. On 1.57 million ClinVar variants it raised AUROC from 0.800 to 0.986 against a same-data, same-backbone post-hoc baseline, and on a shared benchmark its 1.9 million parameters outperformed frozen foundation models with 3 to 1,300 times more parameters.

MELD puts the score difference between wild-type and mutant sequence directly into the supervised objective, instead of training on absolute signal and comparing two sequences after the fact. On 1.57 million ClinVar variants it raised AUROC from 0.800 to 0.986 against a same-data, same-backbone post-hoc baseline, and on a shared benchmark its 1.9 million parameters outperformed frozen foundation models with 3 to 1,300 times more parameters.