Patents by Inventor Emre Guney

Emre Guney has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Publication number: 20250295641
    Abstract: The invention relates to a pharmaceutical composition comprising ibudilast and bumetanide for use in the treatment of autism spectrum disorder (ASD), wherein the composition is administered to a patient showing an overactivation of an NF-?B pathway.
    Type: Application
    Filed: March 25, 2025
    Publication date: September 25, 2025
    Inventors: Lynn Durham, Laura Pérez-Cano, Emre Guney, Francesco Sirci, Xavier Gallego, Samuel Valentini, Jose Manuel Hidalgo
  • Publication number: 20220406405
    Abstract: Systems and techniques can determine candidate treatments for individuals diagnosed with a biological condition. The biological condition can include a neurodevelopmental condition and the candidate treatments can include one or more therapeutics. In one or more implementations, data, such as genetic data, morphological data, and levels of analytes, can be used to group individuals that have been diagnosed with a neurodevelopmental condition based on behavioral classifications. Biological pathways that are disrupted by the neurodevelopmental condition can also be identified along with one or more genes of the biological pathways whose expression is impacted by the neurodevelopmental condition. Therapeutics can be identified to treat individuals diagnosed with the neurodevelopmental condition based on genetic profiles of the therapeutics and genetic profiles of the individuals in which the neurodevelopmental condition is present.
    Type: Application
    Filed: November 16, 2020
    Publication date: December 22, 2022
    Inventors: Lynn Durham, Emre Guney, Laura Perez-Cano, Francesco Sirci, Igor Ariz-Extreme, Mattia Bosio, Daniel Boloc
  • Publication number: 20170270254
    Abstract: Network-based relative proximity measures according to the present invention quantify the closeness between any two sets of nodes (e.g., drug targets and disease genes in a biological network, or groups of people in a social network). The proximity takes into account the scale-free nature of real-world networks and corrects for degree-bias (i.e., due to incompleteness or study biases) by incorporating various distance definitions between the two sets of nodes and comparison of these distances to those of randomly selected nodes in the network (i.e., the distance relative to random expectation), therefore improving processing of the network data. In brief, the proximity offers a formal framework to characterize the distance between two sets of nodes in the network with key applications in various domains from network pharmacology (e.g., discovering novel uses for existing drugs) to social sciences (e.g., defining similarity between groups of individuals).
    Type: Application
    Filed: March 17, 2017
    Publication date: September 21, 2017
    Inventors: Emre Guney, Albert-László Barábasi, Jörg Menche