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Multilayer network construction and analysis pipeline for gene expression data

GSE248963 Homo sapiens Expression profiling by high throughput sequencing 6 samples Submitted 2024/04/01 Platform GPL24676
Summary
Molecular networks are key to understanding the complexity of biological systems. Despite the advances in network construction and analysis techniques, challenges remain in incorporating multidimensional interactions into a hybrid network model and reducing the complexity of large networks into functional modules or influential nodes. Here, we introduce CREAM, a user-friendly application that empowers biologists to construct multilayer networks by integrating gene expression data with various known interactions predicted by experimental and computational techniques, and to identify functional modules and prognostic biomarkers within these networks. When applied to multiple cancer types, CREAM outperforms state-of-the-art module detection methods in identifying biologically relevant modules. Further investigation of colon adenocarcinoma revealed numerous well-known cancer regulators and a promising new therapeutic target, miR-8485. Our in vitro and in vivo experiments demonstrated its inhibitory effects on colon cancer cell proliferation and migration. Overall, CREAM is expected to significantly advance network-based precision medicine research.
Published in
MulNet: a scalable framework for reconstructing intra- and intercellular signaling networks from bulk and single-cell RNA-seq data
Han M, Chen X, Li X et al. · Briefings in bioinformatics 2025 · PMID 40095604 · doi:10.1093/bib/bbaf081
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Also filed as BioProject PRJNA1012745 and SRA study SRP458635. Searching any of these in the dataset finder brings you back here.

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