Bayesian network inference modeling identifies TRIB1 as a novel regulator of cell cycle progression and survival in cancer cells

Results of GNS Healthcare collaboration published in American Association of Cancer Research (AACR)

Learn more about the discovery of novel targets, including TRIB1, which correlates with survival, progression, and metastasis in resistant breast cancer. The study, which was conducted at University of California, San Francisco, utilized the REFS™ (Reverse Engineering and Forward Simulation) causal machine learning and simulation platform to discover novel targets, which creates an avenue for additional research that could lead to more targeted therapeutic interventions with positive implications for the treatment of breast cancer.

GNS  is leading the way, partnering with major names in the healthcare industry to provide value-based solutions such as:

• Subpopulation Analysis
• Disease Mechanisms of Action
• Target Discovery
• Value-based Drug Models
• Intervention Optimization