| Abstrakt: |
A patent application titled "Methods and System for the Reconstruction of Drug Response and Disease Networks and Uses Thereof" has been submitted to the USPTO. The application outlines a method and system that utilizes bioinformatics and computational methods, such as machine learning and deep learning, to identify regulatory drug networks in humans. By analyzing the spatial regulatory interactions within the three-dimensional structure of the human genome, the researchers hope to uncover previously unknown drug pharmacogenomic networks. This approach has the potential to provide insights into the mechanisms of drug effects and facilitate the mapping of drug pathways, eliminating the need for additional experiments in animal or cellular models. The method involves identifying single nucleotide polymorphisms (SNPs) associated with drug response or adverse events, mapping 3D spatial connections using these SNPs, constructing a drug pharmacogenomic network based on target genes, comparing a patient's SNPs to those in the network, and administering the drug if it is deemed effective based on the comparison. The method also includes validating the network, analyzing gene function, mutations, and expression patterns, and organizing the network into functional subsets. The resulting network can be stored in a database for future reference. [Extracted from the article] |
