Tunahan Çakır

This study evaluates RNA-seq's diagnostic utility in three patient groups with non-diagnostic exome sequencing, finding higher yields in groups with candidate variants.

The paper predicts patient-specific metabolite secretion patterns in Parkinson's disease using a novel algorithm, identifies subgroups based on these patterns, and validates the findings with independent data.

This study compares proteomic and metabolomic changes in genetic and environmental Parkinson's disease models, identifying purine metabolism as a shared pathway involved in neurotoxicity.

The paper integrates RNA-seq-based genomic variants and gene expression data to reconstruct personalized metabolic models for Alzheimer's disease, showing improved detection of AD-associated metabolic pathways.

The paper identifies metabolic alterations in Parkinson's disease using human brain transcriptomes and experimental models, finding regional correlations and heterogeneity in metabolic pathways.

The paper develops a genome-scale metabolic model for Drosophila melanogaster to study metabolic disorders and Parkinson's disease.

The paper uses transcriptome data to identify oncogenic signaling pathways targeted by natural products in breast cancer and infers their systemic mechanisms of action.