公开(公告)号：US11573239B2

公开(公告)日：2023-02-07

申请号：US16037949

申请日：2018-07-17

Applicant: BIOINFORMATICS SOLUTIONS INC.

Inventor： Baozhen Shan ,  Ngoc Hieu Tran ,  Ming Li ,  Lei Xin ,  Xianglilan Zhang

IPC: G01N33/48 ,  G01N33/50 ,  G01N33/68 ,  G06F17/16 ,  G16B20/00 ,  G16B40/00 ,  G16B50/00 ,  G16B30/20 ,  G16B40/10 ,  G16B40/20 ,  G16B50/20 ,  G16B50/10

Abstract: The present systems and methods introduce deep learning to de novo peptide sequencing from tandem mass spectrometry data. 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. The present systems and methods are re-trainable to adapt to new sources of data and provides a complete end-to-end training and prediction solution, which is advantageous given the growing massive amount of data. The systems and methods combine deep learning and dynamic programming to solve optimization problems.

公开(公告)号：US20190018019A1

公开(公告)日：2019-01-17

申请号：US16037949

申请日：2018-07-17

Applicant: BIOINFORMATICS SOLUTIONS INC.

Inventor： Baozhen Shan ,  Ngoc Hieu Tran ,  Ming Li ,  Lei Xin ,  Xianglilan Zhang

IPC: G01N33/68 ,  G06F19/18 ,  G06F19/24 ,  G06F19/28 ,  G06F17/16

Abstract: The present systems and methods introduce deep learning to de novo peptide sequencing from tandem mass spectrometry data. 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. The present systems and methods are re-trainable to adapt to new sources of data and provides a complete end-to-end training and prediction solution, which is advantageous given the growing massive amount of data. The systems and methods combine deep learning and dynamic programming to solve optimization problems.