SmCCNet 2.0: A Comprehensive Tool for Multi-omics Network Inference with Shiny Visualization

Abstract excerpt

<h4>Summary</h4> Sparse multiple canonical correlation network analysis (SmCCNet) is a machine learning technique for integrating omics data along with a variable of interest (e.g., phenotype of complex disease), and reconstructing multi-omics networks that are specific to this variable. We present the second-generation SmCCNet (SmCCNet 2.0) that adeptly integrates single or multiple omics data types along with a...

Topics

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• Algorithms
• Bioinformatics and Genomic Networks
• Breast Neoplasms
• Gene Regulatory Networks
• Multifactorial Inheritance
• Multivariate Analysis
• Phenotype
• Signal Transduction

Identifiers and source

Literature Corpus work

4afa4ac9-39d4-503b-8376-821d83c91151

DOI

10.1101/2023.11.20.567893