This figure shows how the STAIG framework can successfully identify spatial domains by integrating image processing and contrastive learning to analyze spatial transcriptomics data effectively.

Spatial transcriptomics and gene expression analysis represent a transformative approach in biomedical research, integrating the spatial context of tissues with high-resolution profiling of gene ...

Biological tissues are made up of different cell types arranged in specific patterns, which are essential to their proper functioning. Understanding these spatial arrangements is important when ...

Genovis AB, a leading provider of innovative enzyme technologies, today announces a strategic partnership with Single Cell Discoveries to broaden the application of the SEQURNA® Thermostable RNase Inh ...

Transcriptomics is the study of the transcriptome, which is the complete set of RNA transcripts produced by the genome at a specific time or under particular conditions. It involves the analysis of ...

Spatial transcriptomics (ST) technologies are applied in biology and medical research for its ability to detect the spatial distribution of transcriptome in histological tissue slices. By probing some ...

Single-cell transcriptomics data from mouse bone-relevant cells was used to inform human bone mineral density genome-wide association studies and prioritize genetic targets with potential causal roles ...

Breast cancer remains one of the most prevalent and life-threatening forms of cancer, impacting millions worldwide. This malignancy's heterogeneity and complexity have long posed significant ...