Single-cell multiomics: technologies and data analysis methods
Advances in single-cell isolation and barcoding technologies offer unprecedented
opportunities to profile DNA, mRNA, and proteins at a single-cell resolution. Recently, bulk …
opportunities to profile DNA, mRNA, and proteins at a single-cell resolution. Recently, bulk …
Applying high-dimensional single-cell technologies to the analysis of cancer immunotherapy
Advances in molecular biology, microfluidics and bioinformatics have empowered the study
of thousands or even millions of individual cells from malignant tumours at the single-cell …
of thousands or even millions of individual cells from malignant tumours at the single-cell …
Machine learning approaches to drug response prediction: challenges and recent progress
Cancer is a leading cause of death worldwide. Identifying the best treatment using
computational models to personalize drug response prediction holds great promise to …
computational models to personalize drug response prediction holds great promise to …
Single-cell RNA analysis reveals the potential risk of organ-specific cell types vulnerable to SARS-CoV-2 infections
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a global
pandemic of coronavirus disease 2019 (COVID-19) since December 2019 that has led to …
pandemic of coronavirus disease 2019 (COVID-19) since December 2019 that has led to …
Transitioning single-cell genomics into the clinic
The use of genomics is firmly established in clinical practice, resulting in innovations across
a wide range of disciplines such as genetic screening, rare disease diagnosis and …
a wide range of disciplines such as genetic screening, rare disease diagnosis and …
ANPELA: Significantly Enhanced Quantification Tool for Cytometry‐Based Single‐Cell Proteomics
Y Zhang, H Sun, X Lian, J Tang, F Zhu - Advanced science, 2023 - Wiley Online Library
ANPELA is widely used for quantifying traditional bulk proteomic data. Recently, there is a
clear shift from bulk proteomics to the single‐cell ones (SCP), for which powerful cytometry …
clear shift from bulk proteomics to the single‐cell ones (SCP), for which powerful cytometry …
STGRNS: an interpretable transformer-based method for inferring gene regulatory networks from single-cell transcriptomic data
J Xu, A Zhang, F Liu, X Zhang - Bioinformatics, 2023 - academic.oup.com
Motivation Single-cell RNA-sequencing (scRNA-seq) technologies provide an opportunity to
infer cell-specific gene regulatory networks (GRNs), which is an important challenge in …
infer cell-specific gene regulatory networks (GRNs), which is an important challenge in …
scREAD: a single-cell RNA-Seq database for Alzheimer's disease
Alzheimer's disease (AD) is a progressive neurodegenerative disorder of the brain and the
most common form of dementia among the elderly. The single-cell RNA-sequencing (scRNA …
most common form of dementia among the elderly. The single-cell RNA-sequencing (scRNA …
BP4RNAseq: a babysitter package for retrospective and newly generated RNA-seq data analyses using both alignment-based and alignment-free quantification …
Processing raw reads of RNA-sequencing (RNA-seq) data, no matter public or newly
sequenced data, involves a lot of specialized tools and technical configurations that are …
sequenced data, involves a lot of specialized tools and technical configurations that are …
Dimensionality reduction and visualization of single-cell RNA-seq data with an improved deep variational autoencoder
Single-cell RNA sequencing (scRNA-seq) is a revolutionary breakthrough that determines
the precise gene expressions on individual cells and deciphers cell heterogeneity and …
the precise gene expressions on individual cells and deciphers cell heterogeneity and …