Hypoxia coordinates the spatial landscape of myeloid cells within glioblastoma to affect survival
Myeloid cells are highly prevalent in glioblastoma (GBM), existing in a spectrum of
phenotypic and activation states. We now have limited knowledge of the tumor …
phenotypic and activation states. We now have limited knowledge of the tumor …
Interpretable deep learning in single-cell omics
Motivation Single-cell omics technologies have enabled the quantification of molecular
profiles in individual cells at an unparalleled resolution. Deep learning, a rapidly evolving …
profiles in individual cells at an unparalleled resolution. Deep learning, a rapidly evolving …
OmicVerse: a framework for bridging and deepening insights across bulk and single-cell sequencing
Single-cell sequencing is frequently affected by “omission” due to limitations in sequencing
throughput, yet bulk RNA-seq may contain these ostensibly “omitted” cells. Here, we …
throughput, yet bulk RNA-seq may contain these ostensibly “omitted” cells. Here, we …
Assessing next-generation sequencing-based computational methods for predicting transcriptional regulators with query gene sets
This article provides an in-depth review of computational methods for predicting
transcriptional regulators (TRs) with query gene sets. Identification of TRs is of utmost …
transcriptional regulators (TRs) with query gene sets. Identification of TRs is of utmost …
scSemiProfiler: Advancing large-scale single-cell studies through semi-profiling with deep generative models and active learning
J Wang, GJ Fonseca, J Ding - Nature Communications, 2024 - nature.com
Single-cell sequencing is a crucial tool for dissecting the cellular intricacies of complex
diseases. Its prohibitive cost, however, hampers its application in expansive biomedical …
diseases. Its prohibitive cost, however, hampers its application in expansive biomedical …
Mixed model-based deconvolution of cell-state abundances (MeDuSA) along a one-dimensional trajectory
Deconvoluting cell-state abundances from bulk RNA-sequencing data can add considerable
value to existing data, but achieving fine-resolution and high-accuracy deconvolution …
value to existing data, but achieving fine-resolution and high-accuracy deconvolution …
Heterogeneous pseudobulk simulation enables realistic benchmarking of cell-type deconvolution methods
Background Computational cell type deconvolution enables the estimation of cell type
abundance from bulk tissues and is important for understanding tissue microenviroment …
abundance from bulk tissues and is important for understanding tissue microenviroment …
GPT-4 Vision on Medical Image Classification--A Case Study on COVID-19 Dataset
arXiv:2310.18498v1 [eess.IV] 27 Oct 2023 Page 1 arXiv:2310.18498v1 [eess.IV] 27 Oct 2023
GPT-4 Vision on Medical Image Classification – A Case Study on COVID-19 Dataset Ruibo …
GPT-4 Vision on Medical Image Classification – A Case Study on COVID-19 Dataset Ruibo …
DISSECT: deep semi-supervised consistency regularization for accurate cell type fraction and gene expression estimation
Cell deconvolution is the estimation of cell type fractions and cell type-specific gene
expression from mixed data. An unmet challenge in cell deconvolution is the scarcity of …
expression from mixed data. An unmet challenge in cell deconvolution is the scarcity of …
Revealing myopathy spectrum: integrating transcriptional and clinical features of human skeletal muscles with varying health conditions
Myopathy refers to a large group of heterogeneous, rare muscle diseases. Bulk RNA-
sequencing has been utilized for the diagnosis and research of these diseases for many …
sequencing has been utilized for the diagnosis and research of these diseases for many …