This study addresses a critical challenge in spatial multi-omics: the effective integration of heterogeneous molecular modalities within complex tissue environments. By introducing SpaDDM, a ...
Artificial intelligence (AI) has become a common tool for bioinformatics, with hundreds of methods published in recent years. Due to the training data demands of deep-learning algorithms, ...
Principles of Flow Cytometry: Gain a solid theoretical foundation in fluidics, optics, fluorescence, and data acquisition. Understand how flow cytometry works and how it applies across biological ...
This repository contains code for the SpatialDIVA method, associated preprocessing, and evaluations performed in the manuscript - "Multi-modal disentanglement of spatial transcriptomics and ...
Layer 2/3 (L2/3) glutamatergic neurons are important sites of experience-dependent plasticity and learning in the mammalian cortex. Their properties vary continuously with cortical depth and depend ...
This repository contains the code of the paper "DeepSpot: Leveraging Spatial Context for Enhanced Spatial Transcriptomics Prediction from H&E Images". Authors: Kalin Nonchev, Sebastian Dawo, Karina ...
The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acs.analchem.4c04462. Averaged mass spectrum from the rat brain tissue with ...
Throughout our lifetime, each beat of the heart requires the coordinated action of multiple cardiac cell types. Understanding cardiac cell biology, its intricate microenvironments, and the mechanisms ...
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