Phys.org

Computational tool incorporates transcriptome size to improve RNA-seq analysis

Researchers studying gene expression have access to vast amounts of data from cells or tissues. This is thanks to advances in bulk and single-cell RNA-sequencing (RNA-seq) technologies that can ...
ascopubs.org

Prediction of Patients With High-Risk Osteosarcoma on the Basis of XGBoost Algorithm Using Transcriptome and Methylation Data From SGH-OS Cohort

Benefits of Combining Circulating Tumor DNA With Tissue and Longitudinal Circulating Tumor DNA Genotyping in Advanced Solid Tumors: SCRUM-Japan MONSTAR-SCREEN-1 Study Osteosarcoma (OS) is the most ...
technologynetworks

Spatial Multiomics: Combining Transcriptome, Proteome, and Epigenome in Tissue

Single-modality spatial data tells only part of the story. Spatial multiomics is extending the promise of spatial biology by capturing the transcriptome, proteome, and epigenome from the same tissue ...
technologynetworks

Integrating Spatial Data With Single-Cell References

Integrating spatial and single-cell data is rapidly becoming a defining step in the spatial biology analysis pipeline. Spatial transcriptomics platforms map gene expression across tissue architecture ...