Author

Minsik Oh

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Open access Aug 2026

Integrative evidence-knowledge marker selection enhances LLM-based cell type annotation in single-cell RNA-seq analysis

CELLIA employs an integrative evidence-knowledge marker selection strategy that combines statistical differential expression criteria with curated tissue-specific marker resources to identify informative marker genes and improves the reliability of LLM-cell type annotation.

Jiyeong Shin, Soyoung Jeong, Hyun Je Kim et al. · BioData Mining · 0 citations

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

Open access Jul 2026

Annotation-free phenotype prediction using knowledge-augmented clustering from single-cell RNA sequencing data

Evaluated across three public scRNA-seq datasets, scCap consistently outperforms baseline models in predictive accuracy and identifies disease-associated subpopulations previously reported in the literature without relying on predefined cell-type annotations.

Janghyun Noh, Yoobin Shin, M. Kim et al. · Briefings in Bioinformatics · 0 citations