Emirhan Tekoglu

The paper develops a motif-based model to predict sequence variant effects in AR enhancers and identifies functional classes of transcription factors, validated against mutagenesis data and GWAS risk alleles.

This study shows that the androgen receptor and MYC work together to control the production of Siglec-7 ligands in prostate cancer by regulating sialylation and glycopeptide profiles.

The paper introduces a method to infer functional regulatory sites in enhancer sequences using STARR-seq data, showing it can identify local regulatory sites missed by global approaches.

This paper evaluates B7-H3 expression across prostate cancer subtypes and identifies it as a stable target for ADC and ICI due to its low heterogeneity and negative regulation by androgen signaling.

This study shows AR-V7 forms condensates independently of androgens and AR-FL in CRPC, driving oncogenic transcription through both condensate-dependent and -independent mechanisms.

The paper analyzes fungal NLR proteins to identify effector domains and amyloid signaling motifs using bioinformatics and structural prediction tools, revealing new domains and expanded amyloid motif families.