Plants are complex systems hierarchically organized and composed of various cell types. To
understand the molecular underpinnings of complex plant systems, single-cell RNA …

In recent years, developing the idea of “cancer big data” has emerged as a result of the
significant expansion of various fields such as clinical research, genomics, proteomics and …

Cell–cell communication is essential to many key biological processes. Intercellular
communication is generally mediated by ligand–receptor interactions (LRIs). Thus, building …

Accurate and consistent estimation of cell-to-cell similarity is crucial for clustering single-cell
RNA-seq (scRNA-seq) data. However, the high sparsity of scRNA-seq data often leads to …

The current state-of-the-art single-cell pre-trained models are greatly inspired by the success
of large language models. They trained transformers by treating genes as tokens and cells …

Single-cell ribonucleic acid sequencing (scRNA-seq) is a high-throughput genomic
technique that is utilized to investigate single-cell transcriptomes. Cluster analysis can …

In recent years, the application of single-cell transcriptomics and spatial transcriptomics
analysis techniques has become increasingly widespread. Whether dealing with single-cell …

Gene expression data are usually known for having a large number of features. Usually,
some of these features are irrelevant and redundant. However, in some cases, all features …

Multicellular organisms have dense affinity with the coordination of cellular activities, which
severely depend on communication across diverse cell types. Cell–cell communication …

Introduction: Long non-coding RNAs (lncRNAs) have been in the clinical use as potential
prognostic biomarkers of various types of cancer. Identifying associations between lncRNAs …