Searching journal content for articles similar to Wang et al. 35 (12): 2744.

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  1. ....scPSS identifies damaged cells and damage progression in mouse infarcted heart tissueWe validated scPSS using single-cell transcriptomic data from mouse hearts before and after myocardial infarction (MI) (Calcagno et al. 2022). The data set contains labeled cardiomyocytes (CMs) from three distinct regions...
  2. .... Recent advancements in single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics (ST) technologies have empowered the comprehensive characterization of gene programs at both single-cell and spatial resolutions. Here, we present DeCEP, a computational framework designed to characterize context...
  3. .... Corresponding authors: chen_jiekai@gibh.ac.cn, lin_lihui@gibh.ac.cnAbstractIntegration of single-cell and spatial transcriptomes represents a fundamental strategy to enhance spatial data quality. However, existing methods for mapping single-cell data to spatial coordinates struggle with large-scale data sets...
  4. ...Harnessing agent-based frameworks in CellAgentChat to unravel cell–cell interactions from single-cell and spatial transcriptomics Vishvak Raghavan1,2,3, Yumin Zheng2, Yue Li1,3 and Jun Ding1,2,3 1School of Computer Science, McGill University, Montreal, Quebec H3A 2A7, Canada; 2Meakins...
  5. ...-guided feature propagation to impute missing gene expression values using spatially informed cell graphs, mitigating data sparsity and gene sensitivity differences. A single-cell foundation model then embeds the data into a unified feature space. LLOKI-CAE further integrates these embeddings across batches using...
  6. ..., rely on short reads and offer the ability to transcriptomically compare different cell types but are limited in their ability to measure differential isoform expression. More recently, long-read sequencing methods have been combined with single-cell and spatial technologies in order to characterize...
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  7. ...state transitions. To gain a more comprehensive understanding of cellular states and gene regulatory mechanisms, researchers have developed single-cell multiomic sequencing technologies (Demetci et al. 2022; Li et al. 2024b). These technologies allow the simultaneous profiling of transcriptomic...
  8. ...intestine, spleen, and thymus, and three different data modalities, which include single-cell RNA-seq (scRNA-seq), single-cell ATAC-seq (scATAC-seq), and spatial transcriptomics (Slide-seq). Figure 1, A through C, presents an overview of GIANT. We first construct gene graphs for cell clusters from each...
  9. ...development, with each technology having varying spatial resolution (subcellular, single-cell, or multicellular regions), gene coverage (targeted vs. whole-transcriptome), and sequencing depth per location. For example, the widely used 10x Genomics Visium platform measures whole transcriptomes from multiple...
  10. ...). In particular, single-cell multi-omics technologies like SHARE-seq (Ma et al. 2020) can simultaneously profile transcriptomic and epigenomic data within individual cells, enabling the interrogation of cellular heterogeneity and molecular hierarchy (Cao et al. 2024). Consequently, numerous methods have emerged...
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