The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Mar. 05, 2024

Filed:

Jun. 09, 2020
Applicant:

Amazon Technologies, Inc., Seattle, WA (US);

Inventors:

Alexander Sewall Ford, Seattle, WA (US);

Vanessa Nguyen, Seattle, WA (US);

Layne Christopher Price, Seattle, WA (US);

Franziska Seeger, Seattle, WA (US);

Yen Ling Adelene Sim, Seattle, WA (US);

Assignee:

Amazon Technologies, Inc., Seattle, WA (US);

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G16B 15/00 (2019.01); G16B 30/20 (2019.01); G16B 40/00 (2019.01);
U.S. Cl.
CPC ...
G16B 15/00 (2019.02); G16B 30/20 (2019.02); G16B 40/00 (2019.02);
Abstract

Techniques for predicting a protein sequence are described. An exemplary method includes receiving a request to predict a missing area of a protein's primary sequence and a corresponding three-dimensional position of the missing area; applying a machine learning model to backbone Cartesian coordinates of the protein's primary sequence and a protein vector of a representation of the protein's primary sequence including the missing area to predict a missing area of the protein primary sequence and a corresponding three-dimensional position for the missing area, wherein the machine learning model is selected from the group consisting of: an attention-based machine learning model, a bidirectional long short term memory-based model, and a convolutional neural network-based model; and outputting a result of the machine learning model.


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