Spatial transcriptomics (ST) is a newly emerging field that integrates high-resolution imaging
and transcriptomic data to enable the high-throughput analysis of the spatial localization of …

Spatially resolved transcriptomics (SRT) is a pioneering method for simultaneously studying
morphological contexts and gene expression at single-cell precision. Data emerging from …

Long noncoding RNAs (lncRNAs) participate in various biological processes and have close
linkages with diseases. In vivo and in vitro experiments have validated many associations …

The identification of drug-target interactions (DTIs) is an essential step in drug discovery. In
vitro experimental methods are expensive, laborious, and time-consuming. Deep learning …

Intercellularcommunication significantly influences tumor progression, metastasis, and
therapy resistance. An intercellular communication inference method includes two main …

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

Drug-disease association prediction is an important part of drug discovery, which can help
researchers uncover potential drug candidates and disease targets more accurately to deal …

Single-cell RNA sequencing (scRNA-seq) has emerged as a powerful tool for investigating
cellular heterogeneity through high-throughput analysis of individual cells. Nevertheless …

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 …