CN112930573A - 疾病类型自动确定方法及电子设备 - Google Patents
疾病类型自动确定方法及电子设备 Download PDFInfo
- Publication number
- CN112930573A CN112930573A CN201980001865.0A CN201980001865A CN112930573A CN 112930573 A CN112930573 A CN 112930573A CN 201980001865 A CN201980001865 A CN 201980001865A CN 112930573 A CN112930573 A CN 112930573A
- Authority
- CN
- China
- Prior art keywords
- gene
- modeling
- genome
- disease type
- sample
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 201000010099 disease Diseases 0.000 title claims abstract description 126
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 title claims abstract description 126
- 238000000034 method Methods 0.000 title claims abstract description 83
- 108090000623 proteins and genes Proteins 0.000 claims abstract description 259
- 230000014509 gene expression Effects 0.000 claims abstract description 114
- 230000000694 effects Effects 0.000 claims abstract description 87
- 238000011156 evaluation Methods 0.000 claims description 20
- 230000008859 change Effects 0.000 claims description 18
- 238000012360 testing method Methods 0.000 claims description 14
- 239000002131 composite material Substances 0.000 claims description 12
- 238000012549 training Methods 0.000 claims description 7
- 238000013528 artificial neural network Methods 0.000 claims description 5
- 238000007637 random forest analysis Methods 0.000 claims description 4
- 238000012706 support-vector machine Methods 0.000 claims description 4
- 230000002301 combined effect Effects 0.000 claims description 3
- 206010028980 Neoplasm Diseases 0.000 description 111
- 239000000523 sample Substances 0.000 description 98
- 210000004027 cell Anatomy 0.000 description 64
- 201000011510 cancer Diseases 0.000 description 35
- 230000004083 survival effect Effects 0.000 description 34
- 230000035772 mutation Effects 0.000 description 24
- 238000011282 treatment Methods 0.000 description 24
- 208000020816 lung neoplasm Diseases 0.000 description 23
- 206010058467 Lung neoplasm malignant Diseases 0.000 description 19
- 201000005202 lung cancer Diseases 0.000 description 19
- 230000001575 pathological effect Effects 0.000 description 18
- 230000035790 physiological processes and functions Effects 0.000 description 18
- 206010027476 Metastases Diseases 0.000 description 16
- 230000009401 metastasis Effects 0.000 description 16
- 239000011159 matrix material Substances 0.000 description 15
- 230000008569 process Effects 0.000 description 15
- 210000001035 gastrointestinal tract Anatomy 0.000 description 12
- 238000004088 simulation Methods 0.000 description 10
- 238000004364 calculation method Methods 0.000 description 9
- 238000004590 computer program Methods 0.000 description 8
- 210000004072 lung Anatomy 0.000 description 8
- 230000001419 dependent effect Effects 0.000 description 7
- 238000010586 diagram Methods 0.000 description 7
- 238000012545 processing Methods 0.000 description 7
- 208000003174 Brain Neoplasms Diseases 0.000 description 6
- 208000006990 cholangiocarcinoma Diseases 0.000 description 6
- 230000003834 intracellular effect Effects 0.000 description 6
- 208000014899 intrahepatic bile duct cancer Diseases 0.000 description 6
- 230000001991 pathophysiological effect Effects 0.000 description 6
- 238000004393 prognosis Methods 0.000 description 6
- 230000009467 reduction Effects 0.000 description 6
- 238000004458 analytical method Methods 0.000 description 5
- 230000003902 lesion Effects 0.000 description 5
- 238000010606 normalization Methods 0.000 description 5
- 238000005516 engineering process Methods 0.000 description 4
- 230000002068 genetic effect Effects 0.000 description 4
- 208000037841 lung tumor Diseases 0.000 description 4
- 230000002829 reductive effect Effects 0.000 description 4
- 238000002560 therapeutic procedure Methods 0.000 description 4
- 208000010507 Adenocarcinoma of Lung Diseases 0.000 description 3
- 210000004556 brain Anatomy 0.000 description 3
- 230000004069 differentiation Effects 0.000 description 3
- 230000006870 function Effects 0.000 description 3
- 230000003993 interaction Effects 0.000 description 3
- 201000005249 lung adenocarcinoma Diseases 0.000 description 3
- 201000010225 mixed cell type cancer Diseases 0.000 description 3
- 208000029638 mixed neoplasm Diseases 0.000 description 3
- 241000894007 species Species 0.000 description 3
- 238000007619 statistical method Methods 0.000 description 3
- 108020004414 DNA Proteins 0.000 description 2
- 206010061818 Disease progression Diseases 0.000 description 2
- 208000031448 Genomic Instability Diseases 0.000 description 2
- 230000004075 alteration Effects 0.000 description 2
- 230000001413 cellular effect Effects 0.000 description 2
- 238000013135 deep learning Methods 0.000 description 2
- 230000007547 defect Effects 0.000 description 2
- 238000011161 development Methods 0.000 description 2
- 230000018109 developmental process Effects 0.000 description 2
- 230000005750 disease progression Effects 0.000 description 2
- 238000002651 drug therapy Methods 0.000 description 2
- 230000007613 environmental effect Effects 0.000 description 2
- 230000008826 genomic mutation Effects 0.000 description 2
- 230000009545 invasion Effects 0.000 description 2
- 239000002207 metabolite Substances 0.000 description 2
- 206010061289 metastatic neoplasm Diseases 0.000 description 2
- 238000013546 non-drug therapy Methods 0.000 description 2
- 150000007523 nucleic acids Chemical class 0.000 description 2
- 230000003287 optical effect Effects 0.000 description 2
- 230000035755 proliferation Effects 0.000 description 2
- 102000004169 proteins and genes Human genes 0.000 description 2
- 230000000717 retained effect Effects 0.000 description 2
- 238000012163 sequencing technique Methods 0.000 description 2
- 230000019491 signal transduction Effects 0.000 description 2
- 230000001225 therapeutic effect Effects 0.000 description 2
- 210000004881 tumor cell Anatomy 0.000 description 2
- 238000007482 whole exome sequencing Methods 0.000 description 2
- 238000012070 whole genome sequencing analysis Methods 0.000 description 2
- 208000024893 Acute lymphoblastic leukemia Diseases 0.000 description 1
- 208000014697 Acute lymphocytic leukaemia Diseases 0.000 description 1
- 208000005623 Carcinogenesis Diseases 0.000 description 1
- 241000282412 Homo Species 0.000 description 1
- 206010027458 Metastases to lung Diseases 0.000 description 1
- 108091028043 Nucleic acid sequence Proteins 0.000 description 1
- 208000006664 Precursor Cell Lymphoblastic Leukemia-Lymphoma Diseases 0.000 description 1
- 208000005718 Stomach Neoplasms Diseases 0.000 description 1
- 230000002159 abnormal effect Effects 0.000 description 1
- 230000004913 activation Effects 0.000 description 1
- 101150010487 are gene Proteins 0.000 description 1
- 239000012472 biological sample Substances 0.000 description 1
- 239000008280 blood Substances 0.000 description 1
- 210000004369 blood Anatomy 0.000 description 1
- 210000001124 body fluid Anatomy 0.000 description 1
- 239000010839 body fluid Substances 0.000 description 1
- 238000004422 calculation algorithm Methods 0.000 description 1
- 230000036952 cancer formation Effects 0.000 description 1
- 231100000504 carcinogenesis Toxicity 0.000 description 1
- 230000024245 cell differentiation Effects 0.000 description 1
- 230000003915 cell function Effects 0.000 description 1
- 230000010261 cell growth Effects 0.000 description 1
- 230000008711 chromosomal rearrangement Effects 0.000 description 1
- 238000002790 cross-validation Methods 0.000 description 1
- 230000003247 decreasing effect Effects 0.000 description 1
- 230000037430 deletion Effects 0.000 description 1
- 238000012217 deletion Methods 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 229940079593 drug Drugs 0.000 description 1
- 239000003814 drug Substances 0.000 description 1
- 239000012634 fragment Substances 0.000 description 1
- 201000006585 gastric adenocarcinoma Diseases 0.000 description 1
- 206010017758 gastric cancer Diseases 0.000 description 1
- 238000003205 genotyping method Methods 0.000 description 1
- 230000012010 growth Effects 0.000 description 1
- 230000005764 inhibitory process Effects 0.000 description 1
- 238000003780 insertion Methods 0.000 description 1
- 230000037431 insertion Effects 0.000 description 1
- 230000000670 limiting effect Effects 0.000 description 1
- 150000002632 lipids Chemical class 0.000 description 1
- 238000010801 machine learning Methods 0.000 description 1
- 229920002521 macromolecule Polymers 0.000 description 1
- 230000036210 malignancy Effects 0.000 description 1
- 230000003211 malignant effect Effects 0.000 description 1
- 238000007620 mathematical function Methods 0.000 description 1
- 230000007246 mechanism Effects 0.000 description 1
- 230000002503 metabolic effect Effects 0.000 description 1
- 229910021645 metal ion Inorganic materials 0.000 description 1
- 230000001394 metastastic effect Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000003012 network analysis Methods 0.000 description 1
- 208000002154 non-small cell lung carcinoma Diseases 0.000 description 1
- 108020004707 nucleic acids Proteins 0.000 description 1
- 102000039446 nucleic acids Human genes 0.000 description 1
- 210000000056 organ Anatomy 0.000 description 1
- 230000000888 organogenic effect Effects 0.000 description 1
- 230000007170 pathology Effects 0.000 description 1
- 230000037361 pathway Effects 0.000 description 1
- 230000035479 physiological effects, processes and functions Effects 0.000 description 1
- 229920000642 polymer Polymers 0.000 description 1
- 238000011946 reduction process Methods 0.000 description 1
- 230000001105 regulatory effect Effects 0.000 description 1
- 230000004044 response Effects 0.000 description 1
- 238000012216 screening Methods 0.000 description 1
- 229940126586 small molecule drug Drugs 0.000 description 1
- 150000003384 small molecules Chemical class 0.000 description 1
- 230000000392 somatic effect Effects 0.000 description 1
- 230000003068 static effect Effects 0.000 description 1
- 238000013179 statistical model Methods 0.000 description 1
- 210000000130 stem cell Anatomy 0.000 description 1
- 201000011549 stomach cancer Diseases 0.000 description 1
- 239000000126 substance Substances 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 238000001356 surgical procedure Methods 0.000 description 1
- 230000009466 transformation Effects 0.000 description 1
- 238000011269 treatment regimen Methods 0.000 description 1
- 208000029729 tumor suppressor gene on chromosome 11 Diseases 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/08—Learning methods
- G06N3/086—Learning methods using evolutionary algorithms, e.g. genetic algorithms or genetic programming
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
- G16H50/20—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N20/00—Machine learning
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/04—Architecture, e.g. interconnection topology
- G06N3/045—Combinations of networks
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H20/00—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
- G16H50/70—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H20/00—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
- G16H20/10—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to drugs or medications, e.g. for ensuring correct administration to patients
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
- G16H50/50—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
Landscapes
- Engineering & Computer Science (AREA)
- Health & Medical Sciences (AREA)
- Data Mining & Analysis (AREA)
- Medical Informatics (AREA)
- Public Health (AREA)
- General Health & Medical Sciences (AREA)
- Biomedical Technology (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- Software Systems (AREA)
- Epidemiology (AREA)
- Primary Health Care (AREA)
- Life Sciences & Earth Sciences (AREA)
- Pathology (AREA)
- Artificial Intelligence (AREA)
- General Physics & Mathematics (AREA)
- General Engineering & Computer Science (AREA)
- Computing Systems (AREA)
- Evolutionary Computation (AREA)
- Mathematical Physics (AREA)
- Databases & Information Systems (AREA)
- Biophysics (AREA)
- Computational Linguistics (AREA)
- Molecular Biology (AREA)
- Bioinformatics & Computational Biology (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Evolutionary Biology (AREA)
- Physiology (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Apparatus Associated With Microorganisms And Enzymes (AREA)
- Measuring Or Testing Involving Enzymes Or Micro-Organisms (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
一种疾病类型自动确定方法和电子设备，所述方法包括：所述电子设备获得被测样本的若干突变基因对预定基因组中每个基因的表达活性的综合影响参数数据(S81)；以及所述电子设备基于所述若干突变基因对预定基因组中每个基因的表达活性的综合影响参数数据，确定所述被测样本对应的疾病类型标签(S82)。
Description
PCT国内申请，说明书已公开。
Claims (10)
- PCT国内申请，权利要求书已公开。
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| PCT/CN2019/104004 WO2021042235A1 (zh) | 2019-09-02 | 2019-09-02 | 疾病类型自动确定方法及电子设备 |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN112930573A true CN112930573A (zh) | 2021-06-08 |
| CN112930573B CN112930573B (zh) | 2024-06-21 |
Family
ID=
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115359040A (zh) * | 2022-09-26 | 2022-11-18 | 至本医疗科技（上海）有限公司 | 预测待测对象的组织样本属性的方法、设备和介质 |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2013026411A1 (zh) * | 2011-08-25 | 2013-02-28 | 深圳华大基因科技有限公司 | 单细胞分类方法、基因筛选方法及其装置 |
| CN105096225A (zh) * | 2014-05-13 | 2015-11-25 | 深圳华大基因研究院 | 辅助疾病诊疗的分析系统、装置及方法 |
| CN105243298A (zh) * | 2015-11-06 | 2016-01-13 | 吴志宏 | 胰腺癌相关癌基因突变信息收集分析系统及分析方法 |
| CN109063418A (zh) * | 2018-07-19 | 2018-12-21 | 东软集团股份有限公司 | 疾病预测分类器的确定方法、装置、设备及可读存储介质 |
| CN109192316A (zh) * | 2018-07-02 | 2019-01-11 | 杭州师范大学 | 一种基于基因网络分析的疾病亚型预测系统 |
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2013026411A1 (zh) * | 2011-08-25 | 2013-02-28 | 深圳华大基因科技有限公司 | 单细胞分类方法、基因筛选方法及其装置 |
| CN105096225A (zh) * | 2014-05-13 | 2015-11-25 | 深圳华大基因研究院 | 辅助疾病诊疗的分析系统、装置及方法 |
| CN105243298A (zh) * | 2015-11-06 | 2016-01-13 | 吴志宏 | 胰腺癌相关癌基因突变信息收集分析系统及分析方法 |
| CN109192316A (zh) * | 2018-07-02 | 2019-01-11 | 杭州师范大学 | 一种基于基因网络分析的疾病亚型预测系统 |
| CN109063418A (zh) * | 2018-07-19 | 2018-12-21 | 东软集团股份有限公司 | 疾病预测分类器的确定方法、装置、设备及可读存储介质 |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115359040A (zh) * | 2022-09-26 | 2022-11-18 | 至本医疗科技（上海）有限公司 | 预测待测对象的组织样本属性的方法、设备和介质 |
| CN115359040B (zh) * | 2022-09-26 | 2023-08-15 | 至本医疗科技（上海）有限公司 | 预测待测对象的组织样本属性的方法、设备和介质 |
Also Published As
| Publication number | Publication date |
|---|---|
| US20220292363A1 (en) | 2022-09-15 |
| WO2021042235A1 (zh) | 2021-03-11 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Shannon et al. | Analyzing microarray data using cluster analysis | |
| US9342657B2 (en) | Methods for predicting an individual's clinical treatment outcome from sampling a group of patient's biological profiles | |
| CN108292326A (zh) | 用于使用多组学癌症谱来识别功能性患者特异性体细胞畸变的整合方法和系统 | |
| US9940383B2 (en) | Method, an arrangement and a computer program product for analysing a biological or medical sample | |
| CN109952611A (zh) | 达沙替尼响应预测模型及其方法 | |
| Dlamini et al. | AI and precision oncology in clinical cancer genomics: From prevention to targeted cancer therapies-an outcomes based patient care | |
| Zhao et al. | Object-oriented regression for building predictive models with high dimensional omics data from translational studies | |
| Bote-Curiel et al. | Text analytics and mixed feature extraction in ovarian cancer clinical and genetic data | |
| US20220292363A1 (en) | Method for automatically determining disease type and electronic apparatus | |
| CN112771618B (zh) | 疾病治疗管理因素特征自动预测方法及电子设备 | |
| Bote-Curiel et al. | A resampling univariate analysis approach to ovarian cancer from clinical and genetic data | |
| CN112930573B (zh) | 疾病类型自动确定方法及电子设备 | |
| CN112840402B (zh) | 获得细胞内确定性事件的方法及电子设备 | |
| US20180181705A1 (en) | Method, an arrangement and a computer program product for analysing a biological or medical sample | |
| US20230046438A1 (en) | Method for predicting cell spatial relation based on single-cell transcriptome sequencing data | |
| US20220215268A1 (en) | Sample analysis method and device based on kernel module in genomic module network | |
| Dudoit et al. | Cluster analysis in DNA microarray experiments | |
| Wang et al. | Adaptation of a Mutual Exclusivity Framework to Identify Driver Mutations within Biological Pathways | |
| Ghadle et al. | Study on analysis of gene expression dataset and identification of differentially expressed genes | |
| Tsai | Applications of Analytics in Disease Prediction Types | |
| Guo et al. | Uncover spatially informed variations for single-cell spatial transcriptomics with STew | |
| Zhang | Bayesian Integrative Analysis Of Omics Data | |
| Hazra et al. | Selection of Certain Cancer Mediating Genes Using a Hybrid Model Logistic Regression Supported by Principal Component Analysis (PC‐LR) | |
| Vajjhala | USING INTERPRETABLE MACHINE LEARNING TO FIND NOVEL GENES USEFUL FOR DISCRIMINATING TUMOR AND NON-TUMOR BREAST CANCER SAMPLES | |
| Bakr et al. | Hybrid Machine Learning Classification for Tipple Negative Breast Cancer |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant |