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Fast, accurate, and versatile data analysis platform for the quantification of molecular spatiotemporal signals.

Our Research / Publications
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Cell. 2025 Apr 04;. doi: 10.1016/j.cell.2025.03.012
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Fast, accurate, and versatile data analysis platform for the quantification of molecular spatiotemporal signals. Ahrens Lab
Mi X, Chen AB, Duarte D, Carey E, Taylor CR, Braaker PN, Bright M, Almeida RG, Lim J, Ruetten VM, Wang Y, Wang M, Zhang W, Zheng W, Reitman ME, Huang Y, Wang X, Li L, Deng H, Shi S, Poskanzer KE, Lyons DA, Nimmerjahn A, Ahrens MB, Yu G
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Abstract

Optical recording of intricate molecular dynamics is becoming an indispensable technique for biological studies, accelerated by the development of new or improved biosensors and microscopy technology. This creates major computational challenges to extract and quantify biologically meaningful spatiotemporal patterns embedded within complex and rich data sources, many of which cannot be captured with existing methods. Here, we introduce activity quantification and analysis (AQuA2), a fast, accurate, and versatile data analysis platform built upon advanced machine-learning techniques. It decomposes complex live-imaging-based datasets into elementary signaling events, allowing accurate and unbiased quantification of molecular activities and identification of consensus functional units. We demonstrate applications across a wide range of biosensors, cell types, organs, animal models, microscopy techniques, and imaging approaches. As exemplar findings, we show how AQuA2 identified drug-dependent interactions between neurons and astroglia, as well as distinct sensorimotor signal propagation patterns in the mouse spinal cord.

Preprint: https://doi.org/10.1101/2024.05.02.592259

PMID: 40203826 [PubMed - indexed for MEDLINE]

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Janelia Authors

Alex Chen
Jing-Xuan Lim
Virginia Ruetten
Misha Ahrens
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