[HTML][HTML] Machine learning for perturbational single-cell omics
Cell biology is fundamentally limited in its ability to collect complete data on cellular
phenotypes and the wide range of responses to perturbation. Areas such as computer vision …
phenotypes and the wide range of responses to perturbation. Areas such as computer vision …
From bench to bedside: Single-cell analysis for cancer immunotherapy
Single-cell technologies are emerging as powerful tools for cancer research. These
technologies characterize the molecular state of each cell within a tumor, enabling new …
technologies characterize the molecular state of each cell within a tumor, enabling new …
APOE4 impairs myelination via cholesterol dysregulation in oligodendrocytes
APOE4 is the strongest genetic risk factor for Alzheimer's disease,–. However, the effects of
APOE4 on the human brain are not fully understood, limiting opportunities to develop …
APOE4 on the human brain are not fully understood, limiting opportunities to develop …
Single-cell multiregion dissection of Alzheimer's disease
Alzheimer's disease is the leading cause of dementia worldwide, but the cellular pathways
that underlie its pathological progression across brain regions remain poorly understood …
that underlie its pathological progression across brain regions remain poorly understood …
Single-cell dissection of the human brain vasculature
Despite the importance of the cerebrovasculature in maintaining normal brain physiology
and in understanding neurodegeneration and drug delivery to the central nervous system …
and in understanding neurodegeneration and drug delivery to the central nervous system …
Single-cell dissection of the human motor and prefrontal cortices in ALS and FTLD
Amyotrophic lateral sclerosis (ALS) and frontotemporal lobar degeneration (FTLD) share
many clinical, pathological, and genetic features, but a detailed understanding of their …
many clinical, pathological, and genetic features, but a detailed understanding of their …
Benchmarking clustering algorithms on estimating the number of cell types from single-cell RNA-sequencing data
Background A key task in single-cell RNA-seq (scRNA-seq) data analysis is to accurately
detect the number of cell types in the sample, which can be critical for downstream analyses …
detect the number of cell types in the sample, which can be critical for downstream analyses …
Single-cell multi-cohort dissection of the schizophrenia transcriptome
The complexity and heterogeneity of schizophrenia have hindered mechanistic elucidation
and the development of more effective therapies. Here, we performed single-cell dissection …
and the development of more effective therapies. Here, we performed single-cell dissection …
Neurons burdened by DNA double-strand breaks incite microglia activation through antiviral-like signaling in neurodegeneration
DNA double-strand breaks (DSBs) are linked to neurodegeneration and senescence.
However, it is not clear how DSB-bearing neurons influence neuroinflammation associated …
However, it is not clear how DSB-bearing neurons influence neuroinflammation associated …
scLENS: data-driven signal detection for unbiased scRNA-seq data analysis
High dimensionality and noise have limited the new biological insights that can be
discovered in scRNA-seq data. While dimensionality reduction tools have been developed …
discovered in scRNA-seq data. While dimensionality reduction tools have been developed …