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RNA sequencing from more than 22 million cells trained a model that predicts cell-type-specific gene expression and noncoding variant...
by Zhexiao Lin, Yuanyuan Gao, Wei Sun Gene-by-gene differential expression analysis is a widely used supervised approach for interpreting single-cell RNA-sequencing (scRNA-seq) da...
RNA sequencing data analyzed with SCITE-RNA enabled reconstruction of cell lineage trees and linked cancer cell evolution to gene expression profiles... The post New method reconst...
A new multi-view learning framework improves clustering of single-cell RNA sequencing data by integrating multiple cellular perspectives to better identify biologically meaningful...
RNA sequencing combined with graph neural networks and Mamba models improves cell type classification, enabling more accurate analysis of complex single-cell datasets... The post G...
RNA sequencing is benefiting from Transformer-based AI models that improve analysis of complex single-cell datasets while supporting more accurate and scalable biological discovery...
TAP-seq combines genome editing with targeted RNA sequencing to enable sensitive and cost-effective single-cell functional genomics screens...
RNA sequencing quality improves with scQCenrich, which combines multiple biological and technical metrics to preserve valuable cells while reducing unnecessary filtering... The pos...
RNA sequencing reveals that immune cells exist along continuous landscapes of changing identities, providing a new framework for understanding cell behavior and improving future im...
Single-cell RNA sequencing is helping researchers uncover cellular responses to fungal pathogens, providing new insights into host-pathogen interactions, biomarkers, and potential...
A multi-model AI framework improves cell type annotation accuracy for single-cell RNA sequencing data, helping researchers interpret complex cellular populations with greater.... T...
A new consortium framework improves how RNA sequencing datasets are standardized, annotated, and shared, enabling more reliable integration and reuse of single-cell transcriptomic...
RNA sequencing workflows using preserved cells enable flexible sample collection and support reproducible single-cell analyses across multiple laboratories and processing platforms...
Advances in RNA sequencing and spatial transcriptomics are revealing complex tumor ecosystems and enabling AI-driven approaches to improve precision immunotherapy and cancer treatm...
RNA sequencing combined with artificial intelligence reconstructed single-cell spatial organization from bulk data, revealing immune barriers that may influence colorectal cancer.....
Advanced RNA sequencing methods, including IRISeq and EnrichSci, uncover spatial interactions and molecular changes linked to aging in vulnerable brain cell populations...
This collection highlights how RNA sequencing is advancing transcriptomics research, from single-cell analysis and disease mechanisms to nanopore sequencing and AI-driven data inte...
RNA sequencing of individual nuclei revealed how stem cells in the Arabidopsis inflorescence meristem commit to distinct developmental fates and establish tissue patterning earlier...
RNA sequencing combined with knowledge distillation improves identification of fine grained T cell subtypes, increasing the accuracy of cancer single cell transcriptomics analyses....
Single-cell RNA sequencing of more than 1.1 million intestinal cells reveals inflammatory drivers, persistent epithelial changes, and new therapeutic targets in Crohn's disease......
RNA sequencing combined with graph adversarial learning improved reconstruction of gene regulatory networks and identified cell type-specific regulators in immune and cancer datase...
STAMP combines imaging and RNA sequencing to link cell morphology with gene expression, enabling researchers to connect molecular profiles directly to observable cellular... The po...
New single-cell method maps protein-DNA interactions, revealing gene regulation changes and advancing multi-omics studies of health and disease.
RNA sequencing and new computational tools enabled construction of a large RNA interactome atlas linking RNA-binding proteins, RNA interactions, and gene regulation...
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