Spatially resolved transcriptomics (SRT) technologies facilitate the exploration of cell fates or states within tissue microenvironments. Despite these advances, the field has not adequately addressed the regulatory heterogeneity influenced by microe...
Single-cell multi-omics techniques, which enable the simultaneous measurement of multiple modalities such as RNA gene expression and Assay for Transposase-Accessible Chromatin (ATAC) within individual cells, have become a powerful tool for decipherin...
The identification of cancer driver genes is crucial for understanding the complex processes involved in cancer development, progression, and therapeutic strategies. Multi-omics data and biological networks provided by numerous databases enable the a...
The interactions between transcription factors (TFs) and the target genes could provide a basis for constructing gene regulatory networks (GRNs) for mechanistic understanding of various biological complex processes. From gene expression data, particu...
Accumulating evidence indicates that long noncoding RNAs (lncRNAs) play important roles in molecular and cellular biology. Although many algorithms have been developed to reveal their associations with complex diseases by using downstream targets, th...
Studying the outcomes of genetic perturbation based on single-cell RNA-seq data is crucial for understanding genetic regulation of cells. However, the high cost of cellular experiments and single-cell sequencing restrict us from measuring the full co...
Primary open-angle glaucoma (POAG) is a common ocular disease, and there is currently no effective treatment for POAG therapy. Thus, identifying some effective diagnostic markers is beneficial to the treatment of patients. The expression profile was ...
Engineering design optimization poses a significant challenge, usually requiring human expertise to discover superior solutions. Although various search techniques have been employed to generate diverse designs, their effectiveness is often limited b...
Identifying potential cancer biomarkers is a key task in biomedical research, providing a promising avenue for the diagnosis and treatment of human tumors and cancers. In recent years, several machine learning-based RNA-disease association prediction...
The discovery of diagnostic and therapeutic biomarkers for complex diseases, especially cancer, has always been a central and long-term challenge in molecular association prediction research, offering promising avenues for advancing the understanding...
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