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:
Sep. 26, 2023

Filed:

Aug. 17, 2021
Applicant:

City University of Hong Kong, Hong Kong, CN;

Inventors:

Zhenhao Sun, Hong Kong, CN;

Meng Wang, Hong Kong, CN;

Shiqi Wang, Hong Kong, CN;

Tak Wu Sam Kwong, Hong Kong, CN;

Assignee:
Attorney:
Primary Examiner:
Int. Cl.
CPC ...
H03M 7/34 (2006.01); G16B 50/50 (2019.01); G16B 40/20 (2019.01); H03M 7/30 (2006.01); G06F 16/22 (2019.01); G06N 7/01 (2023.01);
U.S. Cl.
CPC ...
G16B 50/50 (2019.02); G06F 16/2255 (2019.01); G06N 7/01 (2023.01); G16B 40/20 (2019.02); H03M 7/6011 (2013.01); H03M 7/70 (2013.01);
Abstract

Systems and methods for genome sequence compression and decompression are provided. The method for compression encoding of a genome sequence includes partitioning a genome sequence into a plurality of Group of Bases (GoBs) and processing each of the plurality of GoBs independently to encode the genome sequence into a bit stream. Processing each of the plurality of GoBs includes dividing each of the plurality of GOBs into a first part and a second part, the first part including an initial context part and the second part including a learning-based inference part. The processing each of the plurality of GoBs further includes encoding the first part in accordance with a Markov model, encoding the second part in accordance with a learning-based model, and encoding the encoded first part and the encoded second part into the bit stream with an arithmetic encoder. The learning-based model may include Long and Short-Term Memory (LSTM)-based neural networks.


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