Tahir Mehmood

Multiblock LASSO Framework for Cancer Gene Selection from RNA-Seq PANCAN Data

This study applies Multiblock Lasso to RNA-Seq PANCAN data to select significant genes for cancer classification, demonstrating effective dimensionality reduction and accuracy maintenance.

Integrating Genomic and Environmental Data Using Machine Learning for Vernalization Response Prediction

This study uses Random Forests to predict vernalization response in barley by integrating genomic and environmental data, identifying key factors influencing flowering time.