NETWORK-BASED DEEP LEARNING TECHNOLOGY FOR TARGET IDENTIFICATION AND DRUG REPURPOSING

    公开(公告)号:US20210142173A1

    公开(公告)日:2021-05-13

    申请号:US17096712

    申请日:2020-11-12

    Inventor: Feixiong Cheng

    Abstract: A system to implement a deep learning network model is disclosed. The system includes machine-readable instructions and data that include a biomedical information library comprising information that includes a plurality of drugs, a plurality of biological targets, a plurality of diseases, and a plurality of adverse effects, a biomedical network system comprising a plurality of networks covering chemical, genomic, phenotypic, and cellular profiles, a score prioritizer to determine new targets for the plurality of drugs based on a concatenation of a low-dimensional vector representation for each drug vertex and each biological target vertex, and a model generator configured to generate a deep learning network model that defines a plurality of relationships between the drugs, the biological targets, and the adverse effects. The plurality of relationships defined by the deep learning network model predict drug target identification and drug repurposing.

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