LamineTourelab/MOGONET
MOGONET (Multi-Omics Graph cOnvolutional NETworks) is multi-omics data integrative analysis framework for classification tasks in biomedical applications.
This tool helps researchers in biomedical fields analyze complex biological data by combining different types of 'omics' information, like genomics and proteomics. You input various preprocessed omics datasets and it outputs predictions for specific biological classifications, such as disease subtypes. This is designed for bioinformaticians, computational biologists, and biomedical scientists who need to classify biological samples or identify relevant biomarkers.
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Use this if you need to classify biomedical samples or identify biomarkers by integrating multiple types of omics data (e.g., gene expression, methylation) to gain a more comprehensive understanding than single-omics analysis.
Not ideal if your data is not biomedical or if you only have a single type of omics data for analysis.
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Jupyter Notebook
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MIT
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Last pushed
Mar 27, 2025
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