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100 1 _ |a Bazarova, Alina
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111 2 _ |a ISCB-AFRICA ASBCB 2025
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|d 2025-04-17 - 2025-04-17
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245 _ _ |a Simulation-Based Inference for Computational Biology: Integrating AI, Bayesian Modeling, and HPC
260 _ _ |c 2025
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520 _ _ |a This tutorial introduces Simulation-Based Inference (SBI), a framework combining Bayesian modeling, AI techniques, and high-performance computing (HPC) to address key challenges in computational biology, such as performing reliable inference with limited data by using AI-based approximate Bayesian computation. Moreover, it tackles the problem of intractable likelihood functions, thereby allowing to utilize Bayesian inference for biological systems with multiple sources of stochasticity. The tutorial also demonstrates how to leverage HPC environments to drastically reduce inference runtimes, making it highly relevant for large-scale biological problems. This tutorial bridges theoretical foundations with hands-on applications in computational biology. Participants will learn to implement SBI frameworks using diverse biological models, such as molecular dynamics simulations, agent-based tumor growth models, count data modeling, and Lotka-Volterra systems. Practical exercises in Jupyter notebooks guide attendees through SBI workflows, from simple coin-flipping examples to more complex biological simulations, ensuring accessibility for participants with varied backgrounds. The tutorial’s inclusion of cutting-edge methods like Sequential Neural Posterior Estimation and its emphasis on parallelization and HPC scalability align closely with the scientific community's focus on innovation in computational biology. A previous iteration of the tutorial at the Helmholtz AI Conference 2024 received excellent reviews and led to interdisciplinary discussions, highlighting its broad applicability and impact. For this conference, the content has been further refined with additional examples relevant to the community, ensuring it meets the needs of bioinformatics researchers.
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536 _ _ |a Helmholtz AI Consultant Team FB Information (E54.303.11)
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700 1 _ |a Robledo, Jose Ignacio
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700 1 _ |a Kesselheim, Stefan
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