Patents by Inventor Guillermo Gonzalez-Calderon

Guillermo Gonzalez-Calderon 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).

  • LARGE DATA SET NEGATIVE INFORMATION STORAGE MODEL
    Publication number: 20220207018
    Abstract: Systems and methods for storing large data sets, such as genetic sequence information. Within a “targeted subset” of positions with information, the system stores, both variant states and missing states at each position. Reference states are not stored, but are inferred within the targeted subset when neither a variant nor a missing state is stored at a given position. The absence of a variant state at a given position is assumed to be a reference state. The criteria for missing data are defined in pre-processing and are customizable based on the use case. For example, each data point may represent the genetic information of a sample at a position in the genome. The targeted subset may represent those positions that were included in a sequencing test.
    Type: Application
    Filed: December 13, 2021
    Publication date: June 30, 2022
    Inventors: Jamie K. Teer, Ruizheng Liu, Guillermo Gonzalez-Calderon, Rodrigo Carvajal-Pelaez
  • Large data set negative information storage model
    Patent number: 11216442
    Abstract: Systems and methods for storing large data sets, such as genetic sequence information. Within a “targeted subset” of positions with information, the system stores, both variant states and missing states at each position. Reference states are not stored, but are inferred within the targeted subset when neither a variant nor a missing state is stored at a given position. The absence of a variant state at a given position is assumed to be a reference state. The criteria for missing data are defined in pre-processing and are customizable based on the use case. For example, each data point may represent the genetic information of a sample at a position in the genome. The targeted subset may represent those positions that were included in a sequencing test.
    Type: Grant
    Filed: August 12, 2016
    Date of Patent: January 4, 2022
    Assignee: H. LEE MOFFITT CANCER CENTER AND RESEARCH INSTITUTE, INC
    Inventors: Jamie K. Teer, Ruizheng Liu, Guillermo Gonzalez-Calderon, Rodrigo Carvajal-Pelaez
  • LARGE DATA SET NEGATIVE INFORMATION STORAGE MODEL
    Publication number: 20180239797
    Abstract: Systems and methods for storing large data sets, such as genetic sequence information. Within a “targeted subset” of positions with information, the system stores, both variant states and missing states at each position. Reference states are not stored, but are inferred within the targeted subset when neither a variant nor a missing state is stored at a given position. The absence of a variant state at a given position is assumed to be a reference state. The criteria for missing data are defined in pre-processing and are customizable based on the use case. For example, each data point may represent the genetic information of a sample at a position in the genome. The targeted subset may represent those positions that were included in a sequencing test.
    Type: Application
    Filed: August 12, 2016
    Publication date: August 23, 2018
    Inventors: Jamie K. Teer, Ruizheng Liu, Guillermo Gonzalez-Calderon, Rodrigo Carvajal-Pelaez