Kalya et al., 2022 - Google Patents
Machine Learning based Survival Group Prediction in GlioblastomaKalya et al., 2022
View PDF- Document ID
- 13510706839375809508
- Author
- Kalya M
- Kel A
- Leha A
- Altynbekova K
- Wingender E
- et al.
- Publication year
External Links
Snippet
Glioblastoma (GBM) is a very aggressive malignant brain tumor with the vast majority of patients surviving less than 12 months (Short-term survivors [STS]). Only around 2% of patients survive more than 36 months (Long-term survivors [LTS]). Studying these extreme …
- 208000005017 Glioblastoma 0 title abstract description 57
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
- G06F19/10—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology
- G06F19/18—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology for functional genomics or proteomics, e.g. genotype-phenotype associations, linkage disequilibrium, population genetics, binding site identification, mutagenesis, genotyping or genome annotation, protein-protein interactions or protein-nucleic acid interactions
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
- G06F19/10—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology
- G06F19/24—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology for machine learning, data mining or biostatistics, e.g. pattern finding, knowledge discovery, rule extraction, correlation, clustering or classification
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
- G06F19/10—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology
- G06F19/28—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology for programming tools or database systems, e.g. ontologies, heterogeneous data integration, data warehousing or computing architectures
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
- G06F19/10—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology
- G06F19/12—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology for modelling or simulation in systems biology, e.g. probabilistic or dynamic models, gene-regulatory networks, protein interaction networks or metabolic networks
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
- G06F19/10—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology
- G06F19/20—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology for hybridisation or gene expression, e.g. microarrays, sequencing by hybridisation, normalisation, profiling, noise correction models, expression ratio estimation, probe design or probe optimisation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
- G06F19/10—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology
- G06F19/22—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology for sequence comparison involving nucleotides or amino acids, e.g. homology search, motif or SNP [Single-Nucleotide Polymorphism] discovery or sequence alignment
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
- G06F19/30—Medical informatics, i.e. computer-based analysis or dissemination of patient or disease data
- G06F19/34—Computer-assisted medical diagnosis or treatment, e.g. computerised prescription or delivery of medication or diets, computerised local control of medical devices, medical expert systems or telemedicine
- G06F19/345—Medical expert systems, neural networks or other automated diagnosis
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N33/00—Investigating or analysing materials by specific methods not covered by the preceding groups
- G01N33/48—Investigating or analysing materials by specific methods not covered by the preceding groups biological material, e.g. blood, urine; Haemocytometers
- G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
- G01N33/5005—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving human or animal cells
- G01N33/5008—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving human or animal cells for testing or evaluating the effect of chemical or biological compounds, e.g. drugs, cosmetics
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N33/00—Investigating or analysing materials by specific methods not covered by the preceding groups
- G01N33/48—Investigating or analysing materials by specific methods not covered by the preceding groups biological material, e.g. blood, urine; Haemocytometers
- G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
- G01N33/68—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving proteins, peptides or amino acids
-
- C—CHEMISTRY; METALLURGY
- C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
- C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES OR MICRO-ORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
- C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or micro-organisms; Compositions therefor; Processes of preparing such compositions
- C12Q1/68—Measuring or testing processes involving enzymes, nucleic acids or micro-organisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
- C12Q1/6876—Hybridisation probes
- C12Q1/6883—Hybridisation probes for diseases caused by alterations of genetic material
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N33/00—Investigating or analysing materials by specific methods not covered by the preceding groups
- G01N33/48—Investigating or analysing materials by specific methods not covered by the preceding groups biological material, e.g. blood, urine; Haemocytometers
- G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
- G01N33/53—Immunoassay; Biospecific binding assay
- G01N33/574—Immunoassay; Biospecific binding assay for cancer
- G01N33/57407—Specifically defined cancers
-
- C—CHEMISTRY; METALLURGY
- C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
- C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES OR MICRO-ORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
- C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or micro-organisms; Compositions therefor; Processes of preparing such compositions
- C12Q1/68—Measuring or testing processes involving enzymes, nucleic acids or micro-organisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
- C12Q1/6802—General aspects
- C12Q1/6809—Sequence identification involving differential detection
-
- C—CHEMISTRY; METALLURGY
- C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
- C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES OR MICRO-ORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
- C12Q2600/00—Oligonucleotides characterized by their use
- C12Q2600/158—Expression markers
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Ramirez et al. | Classification of cancer types using graph convolutional neural networks | |
US11043304B2 (en) | Systems and methods for using sequencing data for pathogen detection | |
Jayawardana et al. | Determination of prognosis in metastatic melanoma through integration of clinico‐pathologic, mutation, mRNA, microRNA, and protein information | |
KR20200143462A (en) | Implementing machine learning for testing multiple analytes in biological samples | |
Dhillon et al. | A systematic review on biomarker identification for cancer diagnosis and prognosis in multi-omics: from computational needs to machine learning and deep learning | |
Dohmen et al. | Identifying tumor cells at the single-cell level using machine learning | |
Wang et al. | Breast cancer patient stratification using a molecular regularized consensus clustering method | |
Larsson et al. | Comparative microarray analysis | |
Griffith et al. | A robust prognostic signature for hormone-positive node-negative breast cancer | |
Novianti et al. | Factors affecting the accuracy of a class prediction model in gene expression data | |
Munquad et al. | A deep learning–based framework for supporting clinical diagnosis of glioblastoma subtypes | |
Yaung et al. | Artificial intelligence and high-dimensional technologies in the theragnosis of systemic lupus erythematosus | |
Shi et al. | Systematic analysis of lncRNA and microRNA dynamic features reveals diagnostic and prognostic biomarkers of myocardial infarction | |
US20240167097A1 (en) | Cellular response assays for lung cancer | |
Jo et al. | Distant regulatory effects of genetic variation in multiple human tissues | |
Kalya et al. | Machine Learning based Survival Group Prediction in Glioblastoma | |
Chen et al. | PredMHC: an effective predictor of major histocompatibility complex using mixed features | |
Yang et al. | Pathway activity inference for multiclass disease classification through a mathematical programming optimisation framework | |
Yang et al. | MSPL: Multimodal self-paced learning for multi-omics feature selection and data integration | |
Yang et al. | Pathway-level disease data mining through hyper-box principles | |
Chen et al. | 5-hydroxymethylcytosine signatures in circulating cell-free DNA as early warning biomarkers for COVID-19 progression and myocardial injury | |
Liang et al. | A prognosis-related based method for miRNA selection on liver hepatocellular carcinoma prediction | |
Gan et al. | Identification of differential gene groups from single-cell transcriptomes using network entropy | |
Zhou et al. | Predicting distant metastasis in breast cancer using ensemble classifier based on context-specific miRNA regulation modules | |
Kong et al. | Systematic analysis reveals key microRNAs as diagnostic and prognostic factors in progressive stages of lung cancer |