https://www.selleckchem.com/products/cb-839.html
Cancer subtype identification aims to divide cancer patients into subgroups with distinct clinical phenotypes and facilitate the development for subgroup specific therapies. The massive amount of multi-omics datasets accumulated in the public databases have provided unprecedented opportunities to fulfill this task. As a result, great computational efforts have been made to accurately identify cancer subtypes via integrative analysis of these multi-omics datasets. In this paper, we propose a Consensus Guided Graph Autoencoder (CGGA) to ef
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