4 articles tagged with #variant effect prediction.
On 8,297 held-out MFASS variants, a supervised baseline put 61 splice-disrupting variants in its first 100 and four SpliceAI and Pangolin configurations put 63 to 66. No difference at 100 was established. Pangolin's higher whole-list scores are exploratory and unadjusted. Minigene exon recognition only.
One pretrained genomic model can look dominant on a leaderboard and lose to a linear baseline on the next task. Two evidence ledgers explain why.
Carbon-3B matches Evo2-7B on sequence recovery, variant-effect prediction, and motif-perturbation discrimination while generating DNA over 150 times faster.
AlphaGenome processes 1 million DNA base pairs to predict variant effects across 7,000+ genomic tracks in one second, outperforming specialized models on 25 of 26 VEP benchmarks.
