LeMeDISCO (Large-Scale Molecular Interpretation of Disease Comorbidity), an algorithm that predicts disease comorbidities from shared mode of action (MOA) proteins predicted by the AI-based MEDICASCY algorithm. LeMeDISCO can be used in two different ways: 1.) MEDICASCY-driven LeMeDISCO: The comorbidities for any of the 3,608 diseases from the MEDICASCY provided MOA proteins are predicted. 2.) Pathogenic gene set driven LeMeDISCO: Input your own pathogenic gene set derived from differential gene expression, GWAS, exome analysis, or other experimental/clinical techniques. The LeMeDISCO web service allows users to query the LeMeDISCO database as well as input their own set of pathogenic genes to assess the associated comorbidities, MOA proteins, and pathways.
Notice: This server is freely available to all academic and non-commercial users.
Commercial users – to use this server, or request an evaluation copy, please send an email to Dr. Jeffrey Skolnick: skolnick@gatech.edu.
Commercial users – to use this server, or request an evaluation copy, please send an email to Dr. Jeffrey Skolnick: skolnick@gatech.edu.
Citation: Astore, C, Zhou H, Ilkowski B, Forness J, Skolnick J. 2022. LeMeDISCO: A computational method for large-scale prediction & molecular interpretation of disease comorbidity. Commun Biol. 5, 87. doi.org/10.1038/s42003-022-03816-9. PDF
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Please send questions to Dr. Hongyi Zhou or Courtney Astore.