Prof. Dr. Tunca Doğan Presents Generative AI Research at Purdue University Seminar

Prof. Dr. Tunca Doğan, a faculty member at Hacettepe University’s Department of Computer Science and Artificial Intelligence Engineering, delivered a presentation at the prestigious Purdue University Online Bioinformatics Seminar Series on October 23.

The seminar, titled “Harnessing Generative AI for Biomedical Discovery: Design, Integration, and Insight,” highlighted the Hacettepe Biological Data Science Laboratory’s efforts in using AI-driven methodologies to tackle modern biomedical challenges.

During the talk, Prof. Dr. Doğan introduced DrugGEN, the lab’s end-to-end graph-transformer-based generative adversarial network for designing target-specific drug candidate molecules. He noted that DrugGEN has successfully generated novel inhibitors for the AKT1 protein, which have been validated in vitro.

The presentation also briefly covered FlowProt, a classifier-guided flow-matching model for designing protein backbones, and CROssBARv2, a platform that unifies biomedical data into a queryable knowledge graph, enhanced with LLM-powered natural language interfaces.

Prof. Dr. Doğan, who leads the Hacettepe Biological Data Science Laboratory, was a postdoctoral researcher at EMBL-EBI and Cambridge University before his current role. His research focuses on developing machine and deep learning methods for biomedical data integration, functional prediction, and drug discovery. The seminar was hosted by Prof. Daisuke Kihara of Purdue University.