Razin Rasheed

Using A Machine Learning Algorithm to Identify Risk Genes of Amyotrophic Lateral Sclerosis

Started Sept. 29, 2025

Abstract or project description

Amyotrophic Lateral Sclerosis is a severe and complicated neurodegenerative disease characterized by the progressive loss of neurons, ultimately leading to muscle fatigue and eventually paralysis. There are numerous genetic factors implicatd in ALS, however, the full set of risk genes and their underlying biological mechanisms remain misunderstood. This project aims to use the capabilities of machine learning techniques to identify genes that may contribute to ALS susceptibility.The project involves collecting and preprocessing genomic datasets from ALS patients and healthy controls. Machine learning algorithms will then be applied to detect patterns and highlight genes with strong importance/relevanc. This project seeks to uncover potential ALS risk genes and provide insigts that may help future clinical research in both the Biological study of disease and the implications for the use of machine learning in a biological research setting.