Background Heterogeneity in single-cell RNA-seq (scRNA-seq) data is driven by multiple
sources, including biological variation in cellular state as well as technical variation …

Single-cell RNA sequencing (scRNA-seq) has enabled researchers to study gene
expression at the cellular level. However, due to the extremely low levels of transcripts in a …

Background Pancreatic cancer is a complex disease with a desmoplastic stroma, extreme
hypoxia, and inherent resistance to therapy. Understanding the signaling and adaptive …

There is increasing evidence that changes in the variability or overall distribution of gene
expression are important both in normal biology and in diseases, particularly cancer. Genes …

Background Single-cell RNA sequencing (scRNA-seq) methods have been advantageous
for quantifying cell-to-cell variation by profiling the transcriptomes of individual cells. For …

Deconvolution of mouse transcriptomic data is challenged by the fact that mouse models
carry various genetic and physiological perturbations, making it questionable to assume …

While suppressive antiretroviral therapy can effectively limit HIV-1 replication and evolution,
it leaves behind a residual pool of integrated viral genomes that persist in a state of …

Abstract Between June 9–11, 2019, the International Conference on Intelligent Biology and
Medicine (ICIBM 2019) was held in Columbus, Ohio, USA. The conference included 12 …

Single cell RNA-sequencing (scRNA-seq) technology enables comprehensive
transcriptomic profiling of thousands of cells with distinct phenotypic and physiological states …

Biological functions in cells are highly complicated and heterogenous, and can be reflected
by omics data, such as gene expression levels. Detecting subspace structures in omics data …