BPS2026 Program Book

Exhibitor Presentations Rooms 404AB and 406AB, Moscone Center

Esplanade Room 157: Sunday, February 22 9:30 AM – 11:00 AM Bruker AI Driven Advanced AFM Imaging and Analysis of Cellular and Tissue Samples: Innovations in Large-Area Mapping and Mechanobiology Atomic Force Microscopy (AFM) enables nanoscale mapping of stiffness, adhesion, and viscoelasticity, critical for studying cells, tissues, and biomaterials. Yet, challenges such as sample roughness and limited lateral range restrict large-area mechanobiological imaging. We present an advanced AFM concept integrating SmartMapping with the newly developed CellWizard™ Stage, which coordinates AFM head motors and XYZ-piezo movement for automated, high-precision mapping over a 38 × 38 mm range. Its multi-compartment design accommodates multiple samples, enabling high-throughput, reproducible measurements without user intervention. The AI-guided optical segmentation automatically identifies single cells or regions of interest and generates AFM scan lists, facilitating intelligent navigation and continuous imaging across wells or slides. This combination of SmartMapping and AI segmentation ensures seamless, large-area, and drift-free mechanical mapping. Using this system, we compared Cytochalasin D–treated and control 3T3 fibroblasts, revealing time-lapse mechanical and structural changes. We further characterized 3D SKOV-3 spheroids, zebrafish tumors, and mouse brain tissue, correlating regional mechanical variations with structural organization. Together, these advances establish a new paradigm for automated, intelligent, and large-scale AFM imaging, greatly enhancing throughput and precision in mechanobiology and expanding AFM’s applicability to complex biological systems. Speaker Ming Ye, Applications Scientist, Bruker Nano Surfaces 11:30 AM – 1:00 PM

1:30 PM – 3:00 PM Allen Institute BioFile Finder (BFF): An Easy-to-Use, Web-Based Solution for Sharing Image Data and Increasing Transparency The rapid growth of biological imaging and simulation data has outpaced our ability to efficiently organize, search, and share datasets and results in transparent and reusable ways. Scientific data are often siloed across laboratories, institutions, and storage systems, with critical context locked away in spreadsheets, file paths, or ad hoc metadata conventions. BioFile Finder is an open-source, web-based application addresses this gap by transforming simple, user-provided metadata files into interactive, searchable, and shareable data catalogs—without duplicating large underlying data files. BFF enables researchers to organize, filter, and explore datasets using arbitrary metadata fields, generate reproducible, linkable dataset views, and launch selected files directly into compatible visualization or analysis tools. Although originally developed for large-scale bioimage data, BFF is intentionally data-type agnostic and has also been applied to simulation outputs (e.g. Simularium files), modeling datasets, and even art museum repositories). BioFile Finder is freely available at bff.allencell. org. In this exhibitor presentation, we will demonstrate how BFF can be used in practice to curate datasets underlying figures, publications, and collaborative projects, highlighting real-world use cases across microscopy, modeling, and cross-institutional data sharing. Attendees will see how BFF lowers barriers for non-programmers while supporting reproducibility, provenance, and FAIR data principles through metadata-driven exploration rather than centralized data migration. The session will conclude with an introduction to the Internet of BioImage Data (IBID)—an emerging framework for linking distributed biological datasets through shared metadata rather than centralized storage. We will discuss how tools like BFF can serve as lightweight, user-facing entry points into federated data ecosystems, enabling scalable search, discovery, and reuse across repositories and platforms. This session will highlight both immediately available tools that may be useful in your lab and longer-term infrastructure directions for making complex scientific data easier to find, explore, and reuse, with substantial time reserved for audience questions and discussion. Speakers Gideon Dunster, Scientific Program Manager, Allen Institute Graham Johnson, Senior Director of Visualization and Data Integration, Allen Institute

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