Open access
Jul 2026
scFANCL: Dual contrastive learning with false-negative correction at cell level for single-cell RNA-seq clustering
ScFANCL addresses a key limitation of conventional contrastive learning by applying a cosine-similarity-based threshold to exclude cells of the same type from the negative pool, thereby preserving biological continuity within cell types while maintaining inter-cluster separation.
Gunho Choi, Minsik Oh
· BMC Genomics · 0 citations