Patent
- Patent 1: Method, System, and Storage Medium for Pre-screening Pathogenic Factors of Hyperuricemia Kidney Disease
- Patent 2: Fast Identification Method, System, and Computer-Readable Storage Medium for Gene Data Files
- Patent 3: A Multimodal Omics Data Management System
- Patent 4: Method and System for Automatic Pairing of Gene Sequencing Multisample Data Files
- Patent 5: Medical Artificial Intelligence and High-Performance Computing Resource Scheduling System and Method
- Patent 6: Medical Big Data Sharing Method Based on Federated Learning and Blockchain
Software Copyright
- Software Copyright 1: Automated GWAS Analysis Software Accelerated by HPC Multicore Parallelism
- Software Copyright 2: AutoPheWASpeed Software
- Software Copyright 3: APEAMGA Software
- Software Copyright 4: Vennux Software
- Software Copyright 5: ENA Gene Data Batch Collection Software
Method, System, and Storage Medium for Pre-screening Pathogenic Factors of Hyperuricemia Kidney Disease
Inventors: Chen Yilong; Zeng Xiaoxi; Ying Zhiye; Yu Haopeng; Yang Lina; Kuang Yalan; Gu Yonghong; Ma Liang
Patent Number: ZL202211459944.6
Patent Type: Invention Patent
Grant Date: March 17, 2023
Grant Number: CN115651975B
Main Functions:
Integrated multi-omics analysis with TAD recombination and transcription factor motif enrichment analysis
Realizes a new pre-screening method for pathogenic factors of hyperuricemia kidney disease
Addresses the problem of low accuracy in current pre-screening of pathogenic factors
Fast Identification Method, System, and Computer-Readable Storage Medium for Gene Data Files
Inventors: Chen Yilong; Ying Zhiye; Gu Yonghong; Yu Haopeng; Yang Xuliang; Ge Ping; Cheng Xiaoyu; Yu Pengjia; Cheng Ling; Huang Rong
Patent Number: ZL202211347438.8
Patent Type: Invention Patent
Grant Date: February 3, 2023
Grant Number: CN115391284B
Main Functions:
Accurately, conveniently, and efficiently identify and search for genetic data files
Reduce management errors caused by human factors
Improve the efficiency of computer resource utilization
Enhance personnel management efficiency
A Multimodal Omics Data Management System
Inventors: Gu Yonghong; Ying Zhiye; Chen Yilong; Yu Haopeng; Zhao Shuncun; Li Binjie; Zhang Kaili; Ren Pei; Cheng Xiaoyu; Ge Ping; Zhou Menglin
Patent Number: ZL202210271132.2
Patent Type: Invention Patent
Grant Date: October 20, 2023
Grant Number: CN114627968B
Main Functions:
Proposing an automatic data identification technique based on multi-omics data features and metadata tags
Method and System for Automatic Pairing of Gene Sequencing Multisample Data Files
Inventors: Ying Zhiye; Gu Yonghong; Chen Yilong; Yu Haopeng; Yang Xuliang; Ge Ping; Cheng Xiaoyu; Sheng Jiu; Huang Rong
Patent Number: ZL202210252377.0
Patent Type: Invention Patent
Grant Date: May 24, 2022
Grant Number: CN114328399B
Main Functions:
Rapid and accurate pairing of sample data files
Distinguishing between the same sample template chain file and complementary chain file
Reducing program execution errors caused by human factors
Improving the efficiency of computer resource utilization
Medical Artificial Intelligence and High-Performance Computing Resource Scheduling System and Method
Inventors: Ying Zhiye; Li Chunyang; Chen Yilong; Yu Haopeng; Gong Li; Kuang Yalan
Patent Number: ZL202210133573.6
Patent Type: Invention Patent
Grant Date: April 26, 2022
Grant Number: CN114185689B
Main Functions:
Integrate scheduling of artificial intelligence and high-performance computing resources
Reduce construction costs
Enhance resource utilization
Medical Big Data Sharing Method Based on Federated Learning and Blockchain
Inventors: Kuang Yalan; Zeng Xiaoxi; He Dehuai; Ying Zhiye; Chen Yilong
Patent Number: ZL202210026561.3
Patent Type: Invention Patent
Grant Date: March 22, 2022
Grant Number: CN114048515B
Main Functions:
Proposed node trustworthiness evaluation mechanism
Addressed the issue of untrustworthy nodes in federated learning
Improved the accuracy of federated learning
Achieved secure and high-quality sharing of medical big data
Automated GWAS Analysis Software Accelerated by HPC Multicore Parallelism
Developers:Chen Yilong; Li Chunyang; Ying Zhiye; Kuang Yalan; Zhang Chao; Zeng Xiaoxi
Approval Date: September 11, 2023
Registration Number: 2023SR1042097
Certificate Number: Software Registration No. 11629270
Main Functions:
Efficient Parallel Computing
Automatic Leak Detection and Repair
Customizable SNP Exclusion
Automatic Task Submission
Automatic Result Aggregation
AutoPheWASpeed Software
Developers: Chen Yilong; Li Chunyang; Ying Zhiye; Kuang Yalan; Zhang Chao; Zeng Xiaoxi
Approval Date: September 11, 2023
Registration Number: 2023SR1042093
Certificate Number: Software Registration No. 11629266
Main Functions:
Efficient Parallel Computing
Two PheWAS Calculation Modes
Task Submission Quantity Control
Automatic Task Submission
Automatic Result Aggregation
APEAMGA Software
Developers: Chen Yilong; Zeng Xiaoxi; Hu Yao
Approval Date: May 21, 2021
Registration Number: 2021SR0734178
Certificate Number: Software Registration No. 7456804
Main Functions:
Automated analysis of significant influencing factors in gene big data using generalized additive models
Automated subgroup analysis based on groups
Streamlining the influencing factor analysis process
Faster acquisition of gene data analysis conclusions and visualization results
Vennux Software
Developers: Chen Yilong; Yu Haopeng; Zeng Xiaoxi; Yang Xiaoyan; Li Chunyang; Ying Zhiye; Sun Yajing; Gu Yonghong
Approval Date: April 26, 2021
Registration Number: 2021SR0603596
Certificate Number: Software Registration No. 7326222
Main Function:
Generate Venn diagrams for genomic big data using the Linux system
Address the issue of being unable to generate Venn diagrams on Windows systems due to the massive size of the data
ENA Gene Data Batch Collection Software
Developers: Ying Zhiye; Yu Haopeng; Zeng Xiaoxi; Li Chunyang; Chen Yilong; Sun Yajing; Gu Yonghong
Approval Date: April 26, 2021
Registration Number: 2021SR0597215
Certificate Number: Software Registration No. 7319841
Main Functions:
Batch retrieval of project data download information based on ENA database project numbers
Automatic generation of validation files and download scripts
Reduction of manual effort and time spent on searching ENA project data for download links