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Cao-Berg, I.

Publications and source records attributed to Cao-Berg, I..

2 recordsLinked to original sources

MERFISHEYES: Web-based Visualization and Sharing Platform for Single-cell and Single-molecule Spatial Transcriptomics

Interactive exploration and sharing of hybridization-based spatial transcriptomics datasets remain limited by large file sizes, specialized software, and computationally intensive preprocessing, restricting rapid access to publicly available resources such as the Brain Image Library. Here we present MERFISHEYES (https://merfisheyes.com), a browser-based platform for interactive visualization of single-cell and single-molecule spatial transcriptomics data across commercial and emerging high-throughput platforms. MERFISHEYES enables marker gene exploration, cross-dataset and cross-species comparison, visualization of subcellular RNA localization, and collaborative sharing through browser-accessible links generated directly from drag-and-drop datasets. We use MERFISHEYES to enable browser-based visualization of all 158 spatial transcriptomics datasets in the Brain Image Library and demonstrate its capabilities in handling high-throughput 3D data with genome-scale imputation of gene expression and DNA accessibility. MERFISHEYES provides a scalable framework for rapid exploration, sharing, and collaborative analysis of spatial transcriptomics data.

bioinformatics↗

The Brain Image Library: A Community-Contributed Microscopy Resource for Neuroscientists

Advancements in microscopy techniques and computing technologies have enabled researchers to digitally reconstruct brains at micron scale. As a result, community efforts like the BRAIN Initiative Cell Census Network (BICCN) have generated thousands of whole-brain imaging datasets to trace neuronal circuitry and comprehensively map cell types. This data holds valuable information that extends beyond initial analyses, opening avenues for variation studies and robust classification of cell types in specific brain regions. However, the size and heterogeneity of these imaging data have historically made storage, sharing, and analysis difficult for individual investigators and impractical on a broad community scale. Here, we introduce the Brain Image Library (BIL), a public resource serving the neuroscience community that provides a persistent centralized repository for brain microscopy data. BIL currently holds thousands of brain datasets and provides an integrated analysis ecosystem, allowing for exploration, visualization, and data access without the need to download, thus encouraging scientific discovery and data reuse.

neuroscience↗