IntelliGenes, a unique software developed at Rutgers Health, combines artificial intelligence (AI) and machine learning approaches to measure the significance of specific genomic biomarkers and help predict diseases in individuals, according to the developers.
A study published in Bioinformatics explains how IntelliGenes can be used by a variety of users to analyze multi-genomic and clinical data.
Zeeshan Ahmed, lead author of the study and faculty member at the Rutgers Institute for Health, Health Care Policy and Aging Research (IFH), stated that currently, neither AI nor machine learning tools are available to specifically examine and interpret the entire human genome for lay individuals. Ahmed and members of his Rutgers lab have designed IntelliGenes so that anyone, including students or those without a deep knowledge of bioinformatics techniques or access to high-performance computers, can use the platform.
The software combines traditional statistical methods with state-of-the-art machine learning algorithms to create personalized patient predictions and a visual representation of the biomarkers important for disease prediction.
In another study published in Scientific Reports, researchers used IntelliGenes to discover novel biomarkers and accurately predict cardiovascular diseases.
„In the convergence of data sets and the staggering developments in artificial intelligence and machine learning lies tremendous potential.“
Zeeshan Ahmed, lead author of the study, Assistant Professor of Medicine, Robert Wood Johnson Medical School
„IntelliGenes can support personalized early detection of common and rare diseases in individuals and open paths for more comprehensive research, ultimately leading to new interventions and treatments.“
The researchers tested the software using Amarel, the high-performance computing cluster managed by the Rutgers Office of Advanced Research Computing. The office provides a research computer and data environment for Rutgers researchers involved in complex computational and data-intensive projects.
Co-authors of the study include William DeGroat, Dinesh Mendhe, Atharva Bhusari, and Habiba Abdelhalim from IFH, as well as Saman Zeeshan from the Rutgers Cancer Institute of New Jersey.
DeGroat, W., et al. (2023). IntelliGenes: A novel pipeline for machine learning to discover biomarkers and perform predictive analysis using multi-genomic profiles. Bioinformatics. doi.org/10.1093/bioinformatics/btad755.