ArticleCell cycle (Georgetown, Tex.)2021
Cell-specific gene association network construction from single-cell RNA sequence.
Article in Cell cycle (Georgetown, Tex.), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Immunotherapy and pan-apoptotic characterization of the tumor microenvironment in gastric cancer (STAD): a single-cell multidimensional analysis.Discover oncology · 2024Article
- Single-cell gene regulatory network prediction by explainable AI.Nucleic acids research · 2023Article
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Authors and funding
2 authors.
Funding
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Abstract
The recent development of a high throughput single-cell RNA sequence devises the opportunity to study entire transcriptomes in the smallest detail. It also leads to the characterization of molecules and subtypes of a cell. Cancer epigenetics induced not only from individual molecules but also from the dysfunction of the system and the coupling effect of genes. While rapid advances are being made in the development of tools for single-cell RNA-seq data analysis, few slants are noticed in the potential advantages of single-cell network construction.Here, we used network perturbation theory with significant analysis to develop a cell-specific network that provides an insight into gene-gene association based on molecular expressions in a single-cell resolution. Besides, using this method, we can characterize each cell by inspecting how genes are connected and can identify the hub genes using network degree theory. Pathway & Gene enrichment analysis of the identified cell-specific high network degree genes supported the effectiveness of this method. This method could be beneficial for personalized drug design and even therapeutics.
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