Systems And Methods For Prioritizing The Selection Of Targeted Genes Associated With Diseases For Drug Discovery Based On Human Data

A method for identifying a target gene associated with a disease, comprising the steps of:

• extracting, by a device comprising a memory and a processor in communication with the memory, datasets from a plurality of databases, the extracted datasets comprising historical datasets for a genetic mutation in a human DNA dataset, and/or a gene expression dataset, and/or a gene interaction dataset, and/or a drug dataset, and/or a disease dataset;
• storing, by the device, the extracted datasets in a data lake, the data lake stored in the memory, the data lake stored in graph-based datasets, each of the graph-based datasets comprising a subject and an object and a predicate;
• and
• generating, by the device, a knowledge graph based on the data lake, the knowledge graph representing a plurality of links related to at least one gene and at least one disease.

A non-transitory computer-readable medium including instructions configured to be executed by a processor, wherein the executed instructions are adapted to cause the processor to:

• extract datasets from a plurality of databases, the extracted datasets comprising historical datasets for a genetic mutation in a human DNA dataset, and/or a gene expression dataset, and/or a gene interaction dataset, and/or a drug dataset, and/or a disease dataset;
• store the extracted datasets in a data lake, the data lake stored in a memory in communication with the processor, the data lake stored in graph-based datasets, each of the graph-based datasets comprising a subject and an object and a predicate;
• and
• generate a knowledge graph based on the data lake, the knowledge graph representing a plurality of links related to at least one gene and at least one disease.