Article
In silico generation of synthetic cancer genomes using generative AI.
Cell genomics - 12 Nov 2025
Díaz-Navarro Ander, Zhang Xindi, Jiao Wei, Wang Bo, Stein Lincoln
Abstract excerpt
Understanding how genomic alterations drive cancer is key to advancing precision oncology. To detect these alterations, accurate algorithms are used; however, due to privacy concerns, few deeply sequenced cancer genomes can be shared, limiting benchmarking and representing a major obstacle to the improvement of analytic tools. To address this, we developed OncoGAN, a generative AI model combining adversarial...
Read the complete abstract on PubMedTopics
- Humans
- Neoplasms
- Mutation
- Genomics
- DNA Copy Number Variations
- Computer Simulation
- Algorithms