• Leveraging Large-Scale Perturbome Data for Complex Disease Target Discovery- Sang-Min Park

    B232 Seminar Room, IBS 55 Expo-ro Yuseong-gu, Daejeon, Daejeon, Korea, Republic of

    Complex diseases, such as cancer, sarcopenia, and immune disorders, arise from abnormalities in multiple genes and pathways, posing significant challenges to conventional single-target drug discovery strategies. To address this, we developed a perturbome-based analytical framework that integrates transcriptomic signatures, network pharmacology, and machine learning to identify effective therapeutic candidates. Central to this approach is the

  • Quantifying interventional causality by knockoff operation – Olive Cawiding

    B232 Seminar Room, IBS 55 Expo-ro Yuseong-gu, Daejeon, Daejeon, Korea, Republic of

    In this talk, we discuss the paper, "Quantifying interventional causality by knockoff operation" by Xinyan Zhang and Luonan Chen, Science Advances, 2025. Abstract  Causal inference between measured variables is crucial to understand the underlying mechanism of complex biological processes at a network level but remains challenging in computational biology. We propose an innovative causal criterion,