People communicate with each other, sometimes face to face, sometimes with a text message or phone call. Cells also ...
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 ...
Graph Convolutional Networks (GCNs) are widely applied for spatial domain identification in spatial transcriptomics (ST), where node representations are learned by aggregating information from ...
This repository contains code for the SpatialDIVA method, associated preprocessing, and evaluations performed in the manuscript - "Multi-modal disentanglement of spatial transcriptomics and ...
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, ...
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 ...
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 ...
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