MACHINE LEARNING FOR BIOMARKER DISCOVERY USING NGS DATA - CBIRT

In this article, we will be exploring how machine learning (ML) techniques can be used to identify and analyze biomarkers from next generation sequencing (NGS) data. Biomarkers are specific biological molecules or characteristics that can be used to identify the presence or severity of a particular disease or condition. They play a crucial role in medical diagnosis, treatment, and prognosis, and their discovery and validation is an important area of research in the field of biomedical science. Next Generation Sequencing is a powerful tool that allows researchers to analyze large amounts of genetic data quickly and accurately. By combining the capabilities of machine learning with next generation sequencing data, we can unlock the potential to identify and validate new biomarkers that can improve our understanding of diseases and lead to more effective treatments.