Schedule

Program at a glance

The detailed program will be published closer to the event. The conference runs over three days at DTU, Copenhagen.

Keynote talks

AI for Image-based Systems Biology: From Cryo-Electron Tomography to Virtual Spatial Transcriptomics

Tingying Peng · Helmholtz Munich

Recent advances in biological imaging technologies, including cryo-electron tomography and light-sheet microscopy, are enabling the visualization of cellular structures across multiple spatial and temporal scales. However, extracting quantitative insights from increasingly large and complex datasets remains a major challenge. In this talk, I will present our work on developing artificial intelligence methods for quantitative bioimage analysis. I will highlight our recent work on MemBrain v2, an AI framework for automated analysis of membrane organization in cryo-electron tomography that enables large-scale detection of membrane-associated protein complexes directly in situ. MemBrain integrates automated membrane segmentation, geometry-aware particle detection, and downstream analysis of protein organization. I will also briefly discuss additional projects from our group that develop AI methods for microscopy image enhancement and analysis, including tools for illumination correction, such as BaSiCPy, and light-sheet microscopy data processing, such as the Leonardo-toolset.

Finally, I will present our recent work on Phoenix, a generative AI framework for virtual spatial transcriptomics from routine histology. Phoenix integrates multimodal information across tissue morphology, cell states, and gene expression to infer spatially resolved single-cell molecular profiles in situ. Applied across large patient cohorts and disease contexts, Phoenix enables in silico analysis of treatment response, discovery of spatial biomarkers, and prediction of disease-associated tissue organization. This work extends quantitative biological imaging beyond image enhancement and object detection toward multimodal data integration and predictive modeling of molecular tissue states. Together, these approaches aim to enable scalable, quantitative, and predictive analysis of biological imaging data and facilitate new discoveries in structural, cellular, and spatial biology.

Decoding the tissue ecosystems of the human body

Muzlifah Haniffa · Wellcome Sanger Institute & University of Cambridge

The revolution in single cell genomics, complemented by more recent developments in spatial technologies and artificial intelligence, has changed our understanding of the cellular building blocks of the human body and how our cells form the tissue ecosystems crucial for function. To map the trillions of cells of the body, a large community of researchers from across the globe have assembled under a global consortium, the Human Cell Atlas (HCA). In her talk, Muzlifah Haniffa will discuss the impact of the HCA on modern biomedicine, and then her own work using spatially resolved single-cell genomics and artificial intelligence to decode human development. Her lab has generated the Human Developmental Cell Atlas (HDCA), a unified resource that integrates published and unpublished single-cell/nucleus RNAseq atlases as well as a spatially resolved multimodal cell atlas of 6PCW whole embryos. The HDCA contains ~4.6M cells and ~500 cell types, which were resolved into 94 tissue niches during early development using unsupervised deep learning. This allows description of the development of distributed networks such as the stroma, vasculature and the peripheral nervous system. The HDCA thus provides a holistic window into how human tissue ecosystems are built.

Workshops & satellite sessions

As in previous years, the conference includes hands-on workshops and tutorials on the scverse ecosystem and satellite sessions hosted by partners. Topics and sign-up details will be shared with the full program.