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Heterogeneous Graph Learning for Multi-Omics Cancer Data Integration

Ai Cancer Biology

Graph Neural Networks Cancer Pathway Analysis

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Ai Cancer Biology › Graph Neural Networks Cancer Pathway Analysis

Heterogeneous Graph Learning for Multi-Omics Cancer Data Integration

This research explores heterogeneous graph neural networks that integrate genomic, transcriptomic, proteomic, and metabolomic data as distinct node and edge types. The scientific contribution reveals emergent pathway relationships and synergistic biomarkers invisible to single-omics approaches.

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📚 Academic: Thesis & PPT assistance included🧪 Tech: Master the protocols hands-on📝 Research > 3 months: Publication co-authorship in a Scopus-indexed journal

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