Article

Robust and Interpretable Metagenomic Modeling Through Structure-Aware Multi-View Learning and Attribution-Guided Biological Insight

2026-08-05

Abstract excerpt

<title>Abstract</title> <p>Integrative modeling of metagenomic and clinical data can advance the study of host phenotypes, but remains challenged by cross-view heterogeneity, uncertain generalizability, and poor interpretability. We developed SAMECAT (Structure-Aware Metagenomics multi-viEw Contrastive AlignmenT), a structure-aware deep learning framework that integrates species-level shotgun metagenomic profiles...

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Literature Corpus work: f71fa929-4d19-5f8a-b86e-966ff9cf37fc
DOI: 10.21203/rs.3.rs-9956795/v1

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