Top-down proteomics: Intact proteins are ionized and analyzed directly, allowing for the study of proteoforms and ...

In this paper, we propose an efficient video desnowing spatio-temporal Transformer, which utilizes spatio-temporal sequence attention to parallelly capture intra-frame spatial information ...

The study is useful for advancing spatial transcriptomics through its novel regression-based linear model (glmSMA) that integrates single-cell RNA-seq with spatial reference atlases, though its ...

R package that automatically classifies the cells in the scRNA data by segregating non-malignant cells of tumor microenviroment from the malignant cells. It also infers the copy number profile of ...

Spatial transcriptomics data from tumor sections of responders ... preprocessing of scRNA-seq data According to the standardized pipeline, the scRNA-seq data were processed using the Seurat package ...

EcoNicheS: enhancing ecological niche modeling, niche overlap and connectivity analysis using shiny dashboard and R Package . This is Version 1.0.0, and subsequent versions will be uploaded with ...

Methods: A new Treg signature, Treg.Sig, was created using a computational framework guided by machine learning, utilizing transcriptome data from both single-cell RNA-sequencing (scRNA-seq) and bulk ...

The field of spatial transcriptomics ... “The sequencing-based methods analyze all genes and serve well to provide an unbiased view of tissue ecosystem,” Lundeberg explained. “The hybridization-based ...