Invention Grant
- Patent Title: Computational analysis to predict molecular recognition space of monoclonal antibodies through random-sequence peptide arrays
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Application No.: US17510517Application Date: 2021-10-26
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Publication No.: US11934929B2Publication Date: 2024-03-19
- Inventor: Neal Woodbury
- Applicant: Arizona Board of Regents on behalf of Arizona State University
- Applicant Address: US AZ Scottsdale
- Assignee: ARIZONA BOARD OF REGENTS ON BEHALF OF ARIZONA STATE UNIVERSITY
- Current Assignee: ARIZONA BOARD OF REGENTS ON BEHALF OF ARIZONA STATE UNIVERSITY
- Current Assignee Address: US AZ Scottsdale
- Agency: Quarles & Brady, LLP
- Main IPC: G06N20/10
- IPC: G06N20/10 ; G06N3/08 ; G16B5/00

Abstract:
Methods and systems, including those employing machine learning, utilizing one or more algorithms for relating the structure of a molecule in a library to its function are described. Embodiments described herein relate structure to function by considering the covalent structure of the molecule, the components of that structure that are common to many molecules in the library, and the properties of those components as they relate to the function in question. Applications include, for example, enhancement and amplification of the diagnostic and prognostic signals provided by peptide arrays for use in analyzing the profile of antibodies in the blood produced in response to a disease, condition or treatment.
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