公开(公告)号：US20210317523A1

公开(公告)日：2021-10-14

申请号：US17355823

申请日：2021-06-23

Applicant: KING ABDULLAH UNIVERSITY OF SCIENCE AND TECHNOLOGY

Inventor： Xin GAO ,  Yu LI ,  Sheng WANG ,  Renmin HAN

IPC: C12Q1/6869 ,  G16B40/30 ,  G16B40/10 ,  G16B30/20 ,  G06N3/08

Abstract: A method for sequencing biopolymers. The method includes selecting with a sequence generator module an input nucleotide sequence having plural k-mers; simulating with a deep learning simulator, actual electrical current signals corresponding to the input nucleotide sequence; identifying reads that correspond to the actual electrical current signals; and displaying the reads. The deep learning simulator includes a context-dependent deep learning model that takes into consideration a position of a k-mer of the plural k-mers on the input nucleotide sequence when calculating a corresponding actual electrical current.

公开(公告)号：US20230260593A1

公开(公告)日：2023-08-17

申请号：US17768332

申请日：2020-05-22

Applicant: KING ABDULLAH UNIVERSITY OF SCIENCE AND TECHNOLOGY

Inventor： Xin GAO ,  Yu LI ,  Wenkai HAN

IPC: G16B20/00 ,  G16B40/20 ,  G06N3/08

CPC classification number: G16B20/00 ,  G16B40/20 ,  G06N3/08

Abstract: A method for annotating antibiotic resistance genes includes receiving a raw sequence encoding of a bacterium, determining first, in a level 0 module, whether the raw sequence encoding includes an antibiotic resistance gene (ARG), determining second, in a level 1 module, a resistant drug type, a resistance mechanism, and a gene mobility for the ARG, determining third, in a level 2 module, if the ARG is a beta-lactam, a sub-type of the beta-lactam, and outputting the ARG, the resistant drug type, the resistance mechanism, the gene mobility, and the sub-type of the beta-lactam. The level 0 module, the level 1 module and the level 2 module each includes a deep convolutional neural network (CNN) model.

公开(公告)号：US20220343465A1

公开(公告)日：2022-10-27

申请号：US17848780

申请日：2022-06-24

Applicant: KING ABDULLAH UNIVERSITY OF SCIENCE AND TECHNOLOGY

Inventor： Xin GAO ,  Yu LI ,  Renmin HAN

IPC: G06T3/40 ,  G01N21/64 ,  G06N3/08 ,  G06T5/00 ,  G06T5/20 ,  G06T5/50

Abstract: A method for structure simulation for super-resolution fluorescence microscopy, the method including receiving a first image having a first resolution, which is indicative of a distribution of fluorophores; applying a Markov model to the fluorophores to indicate an emission state of the fluorophores; generating a plurality of second images, having the first resolution, based on the first image and the Markov model; adding DC background to the plurality of second images to generate a plurality of third images, having the first resolution; downsampling the plurality of third images to obtain a plurality of fourth images, which have a second resolution, lower than the first resolution; and generating a time-series, low-resolution images by adding noise to the plurality of fourth images. The time-series, low-resolution images have the second resolution.

公开(公告)号：US20220130541A1

公开(公告)日：2022-04-28

申请号：US17422547

申请日：2020-01-27

Applicant: KING ABDULLAH UNIVERSITY OF SCIENCE AND TECHNOLOGY

Inventor： Xin GAO ,  Yu LI ,  Hiroyuki KUWAHARA

IPC: G16H50/20 ,  G16H50/70 ,  G16H70/60 ,  G06N3/04 ,  G06N3/08 ,  G16B40/00 ,  G16B5/20

Abstract: A method for disease-gene prioritization includes building a heterogenous network to include gene nodes gj and disease nodes di; supplying additional information (xdi, xgj) related to the gene nodes gj and the disease nodes di to generate embeddings zk associated with the gene nodes gj and the disease nodes di; applying a graph convolutional neural network model G to the heterogenous network and to the embeddings zk to calculate aggregated embeddings zk+1; and estimating, with an edge decoder model ED, a probability P of an edge (di, gj), between a selected gene node gj and a selected disease node di. The edge (di, gj) between the selected gene node gj and the selected disease node di is the disease-gene prioritization.

公开(公告)号：US20200035325A1

公开(公告)日：2020-01-30

申请号：US16432123

申请日：2019-06-05

Applicant: KING ABDULLAH UNIVERSITY OF SCIENCE AND TECHNOLOGY

Inventor： Xin GAO ,  Renmin HAN ,  Sheng WANG ,  Yu LI

IPC: G16B30/00

Abstract: A method for global mapping between a first sequence Xp and a second sequence Xg. The method includes receiving the first sequence Xp and the second sequence Xg at a computing device, wherein the first sequence Xp is related to measured raw electrical current signals and the second sequence Xg is related to calculated electrical current signals; applying a continuous wavelet transform (CWT) algorithm to each of the first and second sequences Xp and Xg to obtain raw CWT signals and expected CWT signals, respectively; extracting raw features and expected features from the raw CWT signals and the expected CWT signals, respectively; generating a context-dependent boundary Bi around a previous warping path WI, wherein the previous warping path WI is calculated using a dynamic time warping (DTW) algorithm that relates the raw features to the expected features and I is an index associated with an element of the previous warping path; calculating a new warping path WI−1 based on the context-dependent boundary BI; and identifying a nucleotide sequence associated with the first sequence Xp and the second sequence Xg, based on the new warping path WI−1.

公开(公告)号：US20200370110A1

公开(公告)日：2020-11-26

申请号：US16769127

申请日：2018-10-30

Applicant: KING ABDULLAH UNIVERSITY OF SCIENCE AND TECHNOLOGY

Inventor： Xin GAO ,  Yu LI ,  Sheng WANG ,  Renmin HAN

IPC: C12Q1/6869 ,  G16B40/10 ,  G16B30/20 ,  G16B40/30

Abstract: A method for sequencing biopolymers. The method includes selecting with a sequence generator module an input nucleotide sequence having plural k-mers; simulating with a deep learning simulator, actual electrical current signals corresponding to the input nucleotide sequence; identifying reads that correspond to the actual electrical current signals; and displaying the reads. The deep learning simulator includes a context-dependent deep learning model that takes into consideration a position of a k-mer of the plural k-mers on the input nucleotide sequence when calculating a corresponding actual electrical current.