Applications of single-cell RNA sequencing in drug discovery and development
B Van de Sande, JS Lee, E Mutasa-Gottgens… - Nature Reviews Drug …, 2023 - nature.com
Single-cell technologies, particularly single-cell RNA sequencing (scRNA-seq) methods,
together with associated computational tools and the growing availability of public data …
together with associated computational tools and the growing availability of public data …
Tumor microenvironment: barrier or opportunity towards effective cancer therapy
Tumor microenvironment (TME) is a specialized ecosystem of host components, designed
by tumor cells for successful development and metastasis of tumor. With the advent of 3D …
by tumor cells for successful development and metastasis of tumor. With the advent of 3D …
Spatially informed cell-type deconvolution for spatial transcriptomics
Many spatially resolved transcriptomic technologies do not have single-cell resolution but
measure the average gene expression for each spot from a mixture of cells of potentially …
measure the average gene expression for each spot from a mixture of cells of potentially …
A single-cell atlas of human and mouse white adipose tissue
MP Emont, C Jacobs, AL Essene, D Pant, D Tenen… - Nature, 2022 - nature.com
White adipose tissue, once regarded as morphologically and functionally bland, is now
recognized to be dynamic, plastic and heterogenous, and is involved in a wide array of …
recognized to be dynamic, plastic and heterogenous, and is involved in a wide array of …
Cell type and gene expression deconvolution with BayesPrism enables Bayesian integrative analysis across bulk and single-cell RNA sequencing in oncology
Inferring single-cell compositions and their contributions to global gene expression changes
from bulk RNA sequencing (RNA-seq) datasets is a major challenge in oncology. Here we …
from bulk RNA sequencing (RNA-seq) datasets is a major challenge in oncology. Here we …
Spatial components of molecular tissue biology
Methods for profiling RNA and protein expression in a spatially resolved manner are rapidly
evolving, making it possible to comprehensively characterize cells and tissues in health and …
evolving, making it possible to comprehensively characterize cells and tissues in health and …
Integrating single-cell and spatial transcriptomics to elucidate intercellular tissue dynamics
Single-cell RNA sequencing (scRNA-seq) identifies cell subpopulations within tissue but
does not capture their spatial distribution nor reveal local networks of intercellular …
does not capture their spatial distribution nor reveal local networks of intercellular …
scBERT as a large-scale pretrained deep language model for cell type annotation of single-cell RNA-seq data
Annotating cell types on the basis of single-cell RNA-seq data is a prerequisite for research
on disease progress and tumour microenvironments. Here we show that existing annotation …
on disease progress and tumour microenvironments. Here we show that existing annotation …
Advances in mixed cell deconvolution enable quantification of cell types in spatial transcriptomic data
P Danaher, Y Kim, B Nelson, M Griswold… - Nature …, 2022 - nature.com
Mapping cell types across a tissue is a central concern of spatial biology, but cell type
abundance is difficult to extract from spatial gene expression data. We introduce …
abundance is difficult to extract from spatial gene expression data. We introduce …
Benchmarking of cell type deconvolution pipelines for transcriptomics data
F Avila Cobos, J Alquicira-Hernandez… - Nature …, 2020 - nature.com
Many computational methods have been developed to infer cell type proportions from bulk
transcriptomics data. However, an evaluation of the impact of data transformation, pre …
transcriptomics data. However, an evaluation of the impact of data transformation, pre …