References: Multi-Omics Integration and Graph Analytics

1. Multi-omics - Wikipedia - Overview of multi-omics approaches integrating genomics, transcriptomics, proteomics, and metabolomics data, covering integration strategies and applications in precision medicine and systems biology.

2. Community Structure - Wikipedia - Explains community detection in networks including modularity optimization, Louvain algorithm, and label propagation methods used to identify functional modules in integrated biological networks.

3. Precision Medicine - Wikipedia - Describes how patient-level molecular data and network analysis enable personalized treatment strategies, covering biomarker discovery, patient stratification, and clinical decision support systems.

4. Multi-Omics Data Integration, Interpretation, and Its Application - Davide Chicco - Springer - Practical guide to statistical and network-based methods for integrating heterogeneous omics datasets, covering dimensionality reduction, network fusion, and clinical outcome prediction.

5. Network Science in Medicine and Healthcare - Tiago de Paula Peixoto - Springer - Covers graph analytics methods applied to healthcare including patient similarity networks, disease comorbidity graphs, and community detection for patient stratification.

6. Cytoscape App Store - Cytoscape Consortium - Repository of plugins for biological network analysis including community detection, multi-omics overlay, enrichment visualization, and network comparison tools for integrated analyses.

7. mixOmics Documentation - mixOmics - Documentation for the R package providing multivariate methods for omics data integration, covering sparse PLS, DIABLO multi-block analysis, and network visualization of molecular associations.

8. iGraph R Package - igraph Development Team - Documentation for the igraph library for network analysis, covering community detection algorithms, graph visualization, and network statistics applicable to multi-omics integration networks.

9. SNF: Similarity Network Fusion - University of Toronto - Software for integrating multiple omics data types through patient similarity network fusion, demonstrating graph-based approaches to multi-omics patient stratification.

10. MOFA: Multi-Omics Factor Analysis - Biofam/EMBL - Documentation for the MOFA2 framework for unsupervised integration of multi-omics data, covering factor analysis, variance decomposition, and downstream network analysis of learned factors.