Multi-lineage human iPSC-derived platforms for disease modeling and drug discovery
Human induced pluripotent stem cells (hiPSCs) provide a powerful platform for disease
modeling and have unlocked new possibilities for understanding the mechanisms governing …
modeling and have unlocked new possibilities for understanding the mechanisms governing …
Multiscale understanding of high-energy cathodes in solid-state batteries: from atomic scale to macroscopic scale
In the crucial area of sustainable energy storage, solid-state batteries (SSBs) with
nonflammable solid electrolytes stand out due to their potential benefits of enhanced safety …
nonflammable solid electrolytes stand out due to their potential benefits of enhanced safety …
Defining the relative and combined contribution of CTCF and CTCFL to genomic regulation
Background Ubiquitously expressed CTCF is involved in numerous cellular functions, such
as organizing chromatin into TAD structures. In contrast, its paralog, CTCFL, is normally only …
as organizing chromatin into TAD structures. In contrast, its paralog, CTCFL, is normally only …
Matrix factorization for biomedical link prediction and scRNA-seq data imputation: an empirical survey
Advances in high-throughput experimental technologies promote the accumulation of vast
number of biomedical data. Biomedical link prediction and single-cell RNA-sequencing …
number of biomedical data. Biomedical link prediction and single-cell RNA-sequencing …
Differential expression of single‐cell RNA‐seq data using Tweedie models
The performance of computational methods and software to identify differentially expressed
features in single‐cell RNA‐sequencing (scRNA‐seq) has been shown to be influenced by …
features in single‐cell RNA‐sequencing (scRNA‐seq) has been shown to be influenced by …
scTSSR: gene expression recovery for single-cell RNA sequencing using two-side sparse self-representation
Motivation Single-cell RNA sequencing (scRNA-seq) methods make it possible to reveal
gene expression patterns at single-cell resolution. Due to technical defects, dropout events …
gene expression patterns at single-cell resolution. Due to technical defects, dropout events …
Single-cell RNA sequencing-based computational analysis to describe disease heterogeneity
T Zeng, H Dai - Frontiers in Genetics, 2019 - frontiersin.org
The trillions of cells in the human body can be viewed as elementary but essential biological
units that achieve different body states, but the low resolution of previous cell isolation and …
units that achieve different body states, but the low resolution of previous cell isolation and …
A hybrid deep clustering approach for robust cell type profiling using single-cell RNA-seq data
Single-cell RNA sequencing (scRNA-seq) is a recent technology that enables fine-grained
discovery of cellular subtypes and specific cell states. Analysis of scRNA-seq data routinely …
discovery of cellular subtypes and specific cell states. Analysis of scRNA-seq data routinely …
High-dimensionality data analysis of pharmacological systems associated with complex diseases
It is widely accepted that molecular reductionist views of highly complex human physiologic
activity, eg, the aging process, as well as therapeutic drug efficacy are largely …
activity, eg, the aging process, as well as therapeutic drug efficacy are largely …
SinCWIm: An imputation method for single-cell RNA sequence dropouts using weighted alternating least squares
L Gong, X Cui, Y Liu, C Lin, Z Gao - Computers in Biology and Medicine, 2024 - Elsevier
Background and objectives Single-cell RNA sequencing (scRNA-seq) provides a powerful
tool for exploring cellular heterogeneity, discovering novel or rare cell types, distinguishing …
tool for exploring cellular heterogeneity, discovering novel or rare cell types, distinguishing …