Systems and methods for de novo peptide sequencing from data-independent acquisition using deep learning

US11694769B2 · Bioinformatics Solutions Inc. · priority 2017

Patent US11694769B2 (Bioinformatics Solutions Inc., Active): The present systems and methods introduce deep learning to de novo peptide sequencing from tandem mass spectrometry data, and in particular mass spectrometry data obtained by…
Patent US11694769B2 ↗
Status Active
Priority date 2017-07-17
Filed 2018-12-19
Published (granted) 2023-07-04
Assignee Bioinformatics Solutions Inc.
Claims DeepNovo-DIA
Also published as US20190147983A1

Abstract

The present systems and methods introduce deep learning to de novo peptide sequencing from tandem mass spectrometry data, and in particular mass spectrometry data obtained by data-independent acquisition. The systems and methods achieve improvements in sequencing accuracy over existing systems and methods and enables complete assembly of novel protein sequences without assisting databases. To sequence peptides from mass spectrometry data obtained by data-independent acquisition, precursor profiles representing intensities of one or more precursor ion signals associated with a precursor retention time and fragment ion spectra representing signals from fragment ions and fragment retention times are fed into a neural network.

Why it is here

Claims DeepNovo-DIA: deep learning de novo sequencing of DIA spectra; the inventors are its paper’s authors.

Inventors (7)

Baozhen Shan, Ngoc Hieu Tran, Ming Li, Lei Xin, Rui Qiao, Xin Chen (Waterloo), Chuyi Liu

An inventor links to an author page only where the same person is evident, never on a name alone.

Catalogued papers it cites (23)

Matched from the patent’s 80 literature citations by the rules the paper citation graph uses.

Cited by catalogued patents (1)

  • US11644470B2 Systems and methods for de novo peptide sequencing using deep learning and spectrum pairs

Cited by (32 patent families, 27 organisations)

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