Researchers have developed TranspaceR, an open-source statistical framework that accelerates spatial transcriptomics analysis and addresses key analytical biases across large-scale ...
A new method called CSDE uses a small set of expert-validated cells to correct systematic preprocessing errors in spatial transcriptomics ...
A Nature Methods benchmark of 11 segmentation methods across 15 spatial transcriptomics datasets shows that algorithm and platform choices substantially ...
A new review in PhotoniX Life maps how deep learning is improving fluorescence microscopy across imaging quality, speed, throughput and ...
A comprehensive review in Molecular Systems Biology traces how deep learning, foundation models, and emerging modalities are reshaping image-based profiling, ...
A new computational framework called CellART unifies cell segmentation and cell-type annotation across high-resolution spatial transcriptomics platforms, revealing single-cell detail ...
In a significant leap for spatial transcriptomics, researchers have unveiled DISSECT, an innovative cell segmentation model that fuses cytological imaging ...
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