Temporal modelling using single-cell transcriptomics
Methods for profiling genes at the single-cell level have revolutionized our ability to study
several biological processes and systems including development, differentiation, response …
several biological processes and systems including development, differentiation, response …
Guidelines for bioinformatics of single-cell sequencing data analysis in Alzheimer's disease: review, recommendation, implementation and application
Alzheimer's disease (AD) is the most common form of dementia, characterized by
progressive cognitive impairment and neurodegeneration. Extensive clinical and genomic …
progressive cognitive impairment and neurodegeneration. Extensive clinical and genomic …
Single-cell analysis in rheumatic and allergic diseases: insights for clinical practice
M Nishide, H Shimagami, A Kumanogoh - Nature Reviews Immunology, 2024 - nature.com
Since the advent of single-cell RNA sequencing (scRNA-seq) methodology, single-cell
analysis has become a powerful tool for exploration of cellular networks and dysregulated …
analysis has become a powerful tool for exploration of cellular networks and dysregulated …
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 …
Fast and precise single-cell data analysis using a hierarchical autoencoder
A primary challenge in single-cell RNA sequencing (scRNA-seq) studies comes from the
massive amount of data and the excess noise level. To address this challenge, we introduce …
massive amount of data and the excess noise level. To address this challenge, we introduce …
Gene regulatory network reconstruction: harnessing the power of single-cell multi-omic data
Inferring gene regulatory networks (GRNs) is a fundamental challenge in biology that aims
to unravel the complex relationships between genes and their regulators. Deciphering these …
to unravel the complex relationships between genes and their regulators. Deciphering these …
A comprehensive survey of the approaches for pathway analysis using multi-omics data integration
Pathway analysis has been widely used to detect pathways and functions associated with
complex disease phenotypes. The proliferation of this approach is due to better …
complex disease phenotypes. The proliferation of this approach is due to better …
Graph attention network for link prediction of gene regulations from single-cell RNA-sequencing data
G Chen, ZP Liu - Bioinformatics, 2022 - academic.oup.com
Motivation Single-cell RNA sequencing (scRNA-seq) data provides unprecedented
opportunities to reconstruct gene regulatory networks (GRNs) at fine-grained resolution …
opportunities to reconstruct gene regulatory networks (GRNs) at fine-grained resolution …
spliceJAC: transition genes and state‐specific gene regulation from single‐cell transcriptome data
Extracting dynamical information from single‐cell transcriptomics is a novel task with the
promise to advance our understanding of cell state transition and interactions between …
promise to advance our understanding of cell state transition and interactions between …
Research progress of single-cell transcriptome sequencing in autoimmune diseases and autoinflammatory disease: A review
Autoimmunity refers to the phenomenon that the body's immune system produces antibodies
or sensitized lymphocytes to its own tissues to cause an immune response. Immune …
or sensitized lymphocytes to its own tissues to cause an immune response. Immune …