Biomarkers are essential for disease detection, survival predictions, and treatment decisions, but for many conditions, only a small number of biomarkers are informative, while other diseases have no known useful biomarkers. As technologies advance, researchers seek new ways to understand health and disease through biomarkers, including multiomics and machine learning-based strategies. Combining data from multiple omes and standard clinical parameters with machine learning allows researchers to go beyond basic biomarkers for diagnostics and prognostics.
Download this ebook from The Scientist to learn about the latest multiomics research geared toward discovering or characterizing disease biomarkers, including
- Pairing machine learning and multiomics for biomarker discovery
- Characterizing the ovarian cancer cell-free DNA fragmentome for early detection
- An artificial intelligence-based predictive platform for pancreatic cancer biomarkers
- Harnessing machine learning and population-based genetics to identify disease risk
