Nicole Kuznetsov

CNV-Finder uses deep learning to detect copy number variations from array data, improving accuracy and reducing manual workload for downstream analyses.

This study performs genetic screening of South African Parkinson's disease patients, identifying rare variants and CNVs in known PD genes, highlighting their contribution to disease in an underrepresented population.

CARDBiomedBench evaluates LLM performance in biomedical research using a benchmark focused on neurodegenerative diseases, revealing significant limitations in response quality and safety.

The paper develops epigenetic clocks using long-read DNA methylation data from diverse ancestries, showing improved aging predictions and identifying ancestry-specific aging pathways.

This study investigates the association between COMT genetic variants and Parkinson's disease risk across diverse ancestries but finds no significant enrichment of COMT risk alleles in PD patients after multiple testing correction.

This paper analyzes genetic variation in Parkinson's disease across multiple ancestries, revealing ancestry-specific patterns and highlighting the importance of diverse populations in genetic research.

This study performs APOE-stratified GWAS to uncover genetic mechanisms underlying Alzheimer's disease risk and response to therapies.

GenoTools provides a Python package for genotype data QC, ancestry estimation, and GWAS, enabling scalable and reproducible analysis of large genetic datasets.

Cluster Buster improves SNP genotyping quality by reducing no-calls and enhancing genotype accuracy for neurodegenerative disease research.