User profiles for Kenong Su
 | Kenong SuGrail Verified email at grailbio.com Cited by 484 |
[PDF][PDF] Sliced human cortical organoids for modeling distinct cortical layer formation
Human brain organoids provide unique platforms for modeling development and diseases
by recapitulating the architecture of the embryonic brain. However, current organoid methods …
by recapitulating the architecture of the embryonic brain. However, current organoid methods …
Accurate feature selection improves single-cell RNA-seq cell clustering
Cell clustering is one of the most important and commonly performed tasks in single-cell
RNA sequencing (scRNA-seq) data analysis. An important step in cell clustering is to select a …
RNA sequencing (scRNA-seq) data analysis. An important step in cell clustering is to select a …
[HTML][HTML] A multi-use deep learning method for CITE-seq and single-cell RNA-seq data integration with cell surface protein prediction and imputation
CITE-seq, a single-cell multi-omics technology that measures RNA and protein expression
simultaneously in single cells, has been widely applied in biomedical research, especially in …
simultaneously in single cells, has been widely applied in biomedical research, especially in …
[HTML][HTML] NetAct: a computational platform to construct core transcription factor regulatory networks using gene activity
A major question in systems biology is how to identify the core gene regulatory circuit that
governs the decision-making of a biological process. Here, we develop a computational …
governs the decision-making of a biological process. Here, we develop a computational …
[HTML][HTML] Evaluation of some aspects in supervised cell type identification for single-cell RNA-seq: classifier, feature selection, and reference construction
Background Cell type identification is one of the most important questions in single-cell RNA
sequencing (scRNA-seq) data analysis. With the accumulation of public scRNA-seq data, …
sequencing (scRNA-seq) data analysis. With the accumulation of public scRNA-seq data, …
[PDF][PDF] Pan-cancer analysis of pathway-based gene expression pattern at the individual level reveals biomarkers of clinical prognosis
Identifying biomarkers to predict the clinical outcomes of individual patients is a fundamental
problem in clinical oncology. Multiple single-gene biomarkers have already been identified …
problem in clinical oncology. Multiple single-gene biomarkers have already been identified …
Leveraging information in spatial transcriptomics to predict super-resolution gene expression from histology images in tumors
Recent developments in spatial transcriptomics (ST) technologies have enabled the
profiling of transcriptome-wide gene expression while retaining the location information of …
profiling of transcriptome-wide gene expression while retaining the location information of …
Simulation, power evaluation and sample size recommendation for single-cell RNA-seq
Motivation Determining the sample size for adequate power to detect statistical significance
is a crucial step at the design stage for high-throughput experiments. Even though a number …
is a crucial step at the design stage for high-throughput experiments. Even though a number …
Cell type-specific DNA methylome signatures reveal epigenetic mechanisms for neuronal diversity and neurodevelopmental disorder
DNA methylation plays a critical function in establishing and maintaining cell identity in brain.
Disruption of DNA methylation-related processes leads to diverse neurological disorders. …
Disruption of DNA methylation-related processes leads to diverse neurological disorders. …
[HTML][HTML] Non-linear normalization for non-UMI single cell RNA-Seq
Single cell RNA-seq data, like data from other sequencing technology, contain systematic
technical noise. Such noise results from a combined effect of unequal efficiencies in the …
technical noise. Such noise results from a combined effect of unequal efficiencies in the …