Muhammad Muneeb

PhenotypeToGeneDownloaderR retrieves and validates phenotype-associated genes across multiple databases, achieving high recall and providing a reproducible framework for downstream analysis.

AnnotateMissense integrates and benchmarks missense variant pathogenicity predictors using genome-wide data, achieving high performance with XGBoost.

This study benchmarks 86 heritability estimation configurations and evaluates their impact on polygenic risk score performance across 10 UK Biobank phenotypes.

This paper benchmarks 46 polygenic risk score tools across binary and continuous phenotypes, showing no single method is universally optimal due to varying factors like phenotype architecture and computational demands.

This study benchmarks machine learning, deep learning, and polygenic risk score tools on 80 binary phenotypes from openSNP data to evaluate their predictive performance.

The paper uses machine and deep learning to identify phenotype-associated genes by classifying cases/controls and calculating feature importance, achieving an 84% gene identification ratio.

GWASPoker is a tool that identifies and processes GWAS summary statistics for polygenic risk score calculation by scanning files for column availability without full download.

This paper presents a 9-step pipeline for fine-tuning LLMs on bioinformatics data, demonstrating PRSGPT and BioStarsGPT with performance metrics and QA datasets.