Patents by Inventor Olivier Lichtarge

Olivier Lichtarge 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).

  • Patent number: 10886005
    Abstract: A method and computer system for identifying genes associated with a phenotype includes obtaining data representing mutations in a cohort of subjects exhibiting a phenotype. An evolutionary action (EA) score is calculated for each mutation using the data obtained. For each gene in the cohort, respective distributions of the calculated EA scores are determined for mutations found in the gene. The determined distributions of EA scores are quantitatively compared within the cohort and with random distributions to establish comparison data. Based on the comparison data, distributions of EA scores are identified that are non-random, and linkage of each gene in the cohort to the phenotype is assessed based on the identified non-random distributions to identify genes associated with the phenotype. The phenotype can be a disease, such as cancer, and linkage of each gene in the cohort to the disease can be assessed to identify disease causing genes.
    Type: Grant
    Filed: October 21, 2015
    Date of Patent: January 5, 2021
    Assignee: Baylor College of Medicine
    Inventors: Olivier Lichtarge, Teng-Kuei Hsu, Panagiotis Katsonis, Amanda Michele Koire
  • Patent number: 10300106
    Abstract: An autophagy-inducing compound comprises an autophagy-inducing peptide comprising Beclin 1 peptides immediately N- and C-terminally flanked by moieties R1 and R2, respectively, wherein up to six of said peptide residues may be substituted, R1 and R2 do not naturally flank the Beclin 1 residues, and F270 and F274 are optionally substituted and optionally linked. The compounds may be used to induce autophagy.
    Type: Grant
    Filed: September 3, 2015
    Date of Patent: May 28, 2019
    Assignee: Board of Regents, The University of Texas System
    Inventors: Beth C. Levine, Sanae Shoji-Kawata, Nick V. Grishin, Lisa N. Kinch, Olivier Lichtarge, Angela D. Wilkins
  • Patent number: 9886665
    Abstract: A method, system, and computer program product for event detection using roles and relationships of entities are provided in the illustrative embodiments. A training event and a set of entities participating in the training event are identified in a training data. For a first entity in the set of entities, a first role occupied by the entity in the event is determined. A behavior attribute is assigned to the first role. A relationship of the first role with a second role corresponding to a second entity in the set of entities is determined. An event rule is constructed to detect an event corresponding to the training event in new data and comprising a plurality of roles, behavior attributes, and the relationship. The plurality of roles includes the first role and the second role, and the plurality of behavior attributes includes the behavior attribute assigned to the first role.
    Type: Grant
    Filed: December 8, 2014
    Date of Patent: February 6, 2018
    Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
    Inventors: Ying Chen, Linda H. Kato, Jacques J. Labrie, Meenakshi Nagarajan, William Scott Spangler, Ioana R. Stanoi, Anbu Karani Adikesavan, Benjamin J. Bachman, Lawrence A. Donehower, Olivier Lichtarge, Sam J. Regenbogen, Maria E. Terron-Diaz, Angela D. Wilkins, Curtis R. Pickering
  • Publication number: 20170316148
    Abstract: A method and computer system for identifying genes associated with a phenotype includes obtaining data representing mutations in a cohort of subjects exhibiting a phenotype. An evolutionary action (EA) score is calculated for each mutation using the data obtained. For each gene in the cohort, respective distributions of the calculated EA scores are determined for mutations found in the gene. The determined distributions of EA scores are quantitatively compared within the cohort and with random distributions to establish comparison data. Based on the comparison data, distributions of EA scores are identified that are non-random, and linkage of each gene in the cohort to the phenotype is assessed based on the identified non-random distributions to identify genes associated with the phenotype. The phenotype can be a disease, such as cancer, and linkage of each gene in the cohort to the disease can be assessed to identify disease causing genes.
    Type: Application
    Filed: October 21, 2015
    Publication date: November 2, 2017
    Inventors: Olivier Lichtarge, Teng-Kuei Hsu, Panagiotis Katsonis, Amanda Michele Koire
  • Patent number: 9720902
    Abstract: A new information in a language and relating to a subject matter domain is parsed into a constituent set of complete grammatical constructs. In a subset of the complete grammatical constructs, a set of linguistic styles of the language is identified according to a subset of a set of word-style associations related to the language and independent of the subject matter domain. A first weight is assigned to a first linguistic style and a second weight to a second linguistic style from the set of linguistic styles. A first intention information is mapped to the first style using a first style-intention rule, and a second intention information to the second style using a second style-intention rule. A complete grammatical construct in the subset is tagged with the first intention information responsive to a weight associated with the first intention information exceeding an intention selection threshold.
    Type: Grant
    Filed: March 16, 2016
    Date of Patent: August 1, 2017
    Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
    Inventors: Meenakshi Nagarajan, William Scott Spangler, Benjamin J. Bachman, Lawrence A. Donehower, Olivier Lichtarge, Sam J. Regenbogen, Angela D. Wilkins, Curtis R. Pickering
  • Publication number: 20160203118
    Abstract: A new information in a language and relating to a subject matter domain is parsed into a constituent set of complete grammatical constructs. In a subset of the complete grammatical constructs, a set of linguistic styles of the language is identified according to a subset of a set of word-style associations related to the language and independent of the subject matter domain. A first weight is assigned to a first linguistic style and a second weight to a second linguistic style from the set of linguistic styles. A first intention information is mapped to the first style using a first style-intention rule, and a second intention information to the second style using a second style-intention rule. A complete grammatical construct in the subset is tagged with the first intention information responsive to a weight associated with the first intention information exceeding an intention selection threshold.
    Type: Application
    Filed: March 16, 2016
    Publication date: July 14, 2016
    Applicants: International Business Machines Corporation, Baylor College of Medicine, The Board of Regents, The University of Texas System
    Inventors: Meenakshi Nagarajan, William Scott Spangler, Benjamin J. Bachman, Lawrence A. Donehower, Olivier Lichtarge, Sam J. Regenbogen, Angela D. Wilkins, Curtis R. Pickering
  • Publication number: 20160162465
    Abstract: A new information in a language and relating to a subject matter domain is parsed into a constituent set of complete grammatical constructs. In a subset of the complete grammatical constructs, a set of linguistic styles of the language is identified according to a subset of a set of word-style associations related to the language and independent of the subject matter domain. A first weight is assigned to a first linguistic style and a second weight to a second linguistic style from the set of linguistic styles. A first intention information is mapped to the first style using a first style-intention rule, and a second intention information to the second style using a second style-intention rule. A complete grammatical construct in the subset is tagged with the first intention information responsive to a weight associated with the first intention information exceeding an intention selection threshold.
    Type: Application
    Filed: December 8, 2014
    Publication date: June 9, 2016
    Applicants: International Business Machines Corporation, Baylor College of Medicine, The Board of Regents, The University of Texas System
    Inventors: MEENAKSHI NAGARAJAN, William Scott Spangler, Benjamin J. Bachman, Lawrence A. Donehower, Olivier Lichtarge, Sam J. Regenbogen, Angela D. Wilkins, Curtis R. Pickering
  • Publication number: 20160162788
    Abstract: A method, system, and computer program product for event detection using roles and relationships of entities are provided in the illustrative embodiments. A training event and a set of entities participating in the training event are identified in a training data. For a first entity in the set of entities, a first role occupied by the entity in the event is determined. A behavior attribute is assigned to the first role. A relationship of the first role with a second role corresponding to a second entity in the set of entities is determined. An event rule is constructed to detect an event corresponding to the training event in new data and comprising a plurality of roles, behavior attributes, and the relationship. The plurality of roles includes the first role and the second role, and the plurality of behavior attributes includes the behavior attribute assigned to the first role.
    Type: Application
    Filed: December 8, 2014
    Publication date: June 9, 2016
    Applicants: International Business Machines Corporation, Baylor College of Medicine, The Board of Regents, The University of Texas System
    Inventors: Ying Chen, Linda H. Kato, Jacques J. Labrie, Meenakshi Nagarajan, William Scott Spangler, Ioana R. Stanoi, Anbu Karani Adikesavan, Benjamin J. Bachman, Lawrence A. Donehower, Olivier Lichtarge, Sam J. Regenbogen, Maria E. Terron-Diaz, Angela D. Wilkins, Curtis R. Pickering
  • Patent number: 9355089
    Abstract: A new information in a language and relating to a subject matter domain is parsed into a constituent set of complete grammatical constructs. In a subset of the complete grammatical constructs, a set of linguistic styles of the language is identified according to a subset of a set of word-style associations related to the language and independent of the subject matter domain. A first weight is assigned to a first linguistic style and a second weight to a second linguistic style from the set of linguistic styles. A first intention information is mapped to the first style using a first style-intention rule, and a second intention information to the second style using a second style-intention rule. A complete grammatical construct in the subset is tagged with the first intention information responsive to a weight associated with the first intention information exceeding an intention selection threshold.
    Type: Grant
    Filed: December 8, 2014
    Date of Patent: May 31, 2016
    Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
    Inventors: Meenakshi Nagarajan, William Scott Spangler, Benjamin J. Bachman, Lawrence A. Donehower, Olivier Lichtarge, Sam J. Regenbogen, Angela D. Wilkins, Curtis R. Pickering
  • Publication number: 20150359840
    Abstract: An autophagy-inducing compound comprises an autophagy-inducing peptide comprising Beclin 1 peptides immediately N- and C-terminally flanked by moieties R1 and R2, respectively, wherein up to six of said peptide residues may be substituted, R1 and R2 do not naturally flank the Belclin 1 residues, and F270 and F274 are optionally substituted and optionally linked. The compounds may be used to induce autophagy.
    Type: Application
    Filed: September 3, 2015
    Publication date: December 17, 2015
    Applicants: BAYLOR COLLEGE OF MEDICINE, BOARD OF REGENTS, THE UNIVERSITY OF TEXAS SYSTEM
    Inventors: Beth C. Levine, Sanae Shoji-Kawata, Nick V. Grishin, Lisa N. Kinch, Olivier Lichtarge, Angela D. Wilkins
  • Patent number: 8802633
    Abstract: An autophagy-inducing compound comprises an autophagy-inducing peptide comprising Beclin 1 residues 269-279 immediately N- and C-terminally flanked by moieties R1 and R2, respectively, wherein up to six of said residues may be substituted, R1 and R2 do not naturally flank the Belclin 1 residues, and F270 and F274 are optionally substituted and optionally linked. The compounds may be used to induce autophagy.
    Type: Grant
    Filed: November 8, 2013
    Date of Patent: August 12, 2014
    Assignees: Board of Regents, The University of Texas System, Baylor College of Medicine
    Inventors: Beth C. Levine, Sanae Shoji-Kawata, Olivier Lichtarge, Angela D. Wilkins, Nick V. Grishin, Lisa N. Kinch
  • Patent number: 8722628
    Abstract: An autophagy-inducing compound comprises an autophagy-inducing peptide comprising beclin-1 residues 269-283 and a heterologous moiety that promotes therapeutic stability or delivery of the compound. The compound may be used to induce autophagy and in assays with beclin-1 binding partners.
    Type: Grant
    Filed: November 8, 2013
    Date of Patent: May 13, 2014
    Assignee: Board of Regents, The University of Texas System
    Inventors: Beth C. Levine, Sanae Shoji-Kawata, Olivier Lichtarge, Angela D. Wilkins
  • Publication number: 20140066382
    Abstract: An autophagy-inducing compound comprises an autophagy-inducing peptide comprising beclin-1 residues 269-283 and a heterologous moiety that promotes therapeutic stability or delivery of the compound. The compound may be used to induce autophagy and in assays with beclin-1 binding partners.
    Type: Application
    Filed: November 8, 2013
    Publication date: March 6, 2014
    Applicants: Baylor College of Medicine, Board of Regents, The University of Texas System
    Inventors: Beth C. Levine, Sanae Shoji-Kawata, Olivier Lichtarge, Angela D. Wilkins
  • Publication number: 20040023296
    Abstract: The present invention relates to methods to determine functional sites of a sequence using quantitative ET analysis. More particularly, the quantitative ET analysis utilizes gap tolerance and clustering statistics to determine the functional sites.
    Type: Application
    Filed: November 27, 2002
    Publication date: February 5, 2004
    Applicant: Baylor College of Medicine
    Inventor: Olivier Lichtarge