Single-cell transcriptomics is rapidly advancing our understanding of the composition of
complex tissues and biological cells, and single-cell RNA sequencing (scRNA-seq) holds …

Background Identification of the cancer subtype plays a crucial role to provide an accurate
diagnosis and proper treatment to improve the clinical outcomes of patients. Recent studies …

Motivation Cell-type annotation is fundamental in revealing cell heterogeneity for single-cell
data analysis. Although a host of works have been developed, the low signal-to-noise-ratio …

Human cancers present a significant public health challenge and require the discovery of
novel drugs through translational research. Transcriptomics profiling data that describes …

Machine learning techniques have become increasingly important in analyzing single-cell
RNA and identifying cell types, providing valuable insights into cellular development and …

阐明人类胚胎发育的分子调控机制一直是科学家们努力攻克的重大生物学问题之一. 然而,
由于人类胚胎样本稀少, 样本解剖困难, 器官结构复杂等因素, 解析人类胚胎发育机制面临重重 …

This paper aims to review the current method-ologies, advancements, and future directions
in applications of Machine learning in Single-cell Sequencing of Cancer tumors, which will …

Background The advent of single-cell RNA sequencing (scRNA-seq) has provided a high-
resolution overview of the cellular heterogeneity of different tissue types. Manual cell type …