Mayoral-Peña et al., 2023 - Google Patents
Identification of biomarkers for breast cancer early diagnosis based on the molecular classification using machine learning algorithms on transcriptomic data and …Mayoral-Peña et al., 2023
- Document ID
- 9549607866929620847
- Author
- Mayoral-Peña K
- Peña O
- Artzi N
- de Donato M
- Publication year
External Links
Snippet
Background: Breast cancer is the second leading cause of global female mortality. Diagnosing and treating breast cancer patients at early stages is relevant for providing successful treatment and increasing the patient's survival rate. The use of new analytical …
Classifications
-
- 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
- C12Q1/6876—Hybridisation probes
- C12Q1/6883—Hybridisation probes for diseases caused by alterations of genetic material
- C12Q1/6886—Hybridisation probes for diseases caused by alterations of genetic material for cancer
-
- 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
- G06F19/18—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
- G06F19/20—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
- G06F19/28—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
- 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
-
- 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
- G06F19/30—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
-
- 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 |
---|---|---|
Wei et al. | Intratumoral and intertumoral genomic heterogeneity of multifocal localized prostate cancer impacts molecular classifications and genomic prognosticators | |
Simon et al. | Analysis of gene expression data using BRB-array tools | |
Győrffy et al. | Multigene prognostic tests in breast cancer: past, present, future | |
Azim Jr et al. | Utility of prognostic genomic tests in breast cancer practice: The IMPAKT 2012 Working Group Consensus Statement | |
Pusztai et al. | Molecular classification of breast cancer: limitations and potential | |
Wang et al. | The bimodality index: a criterion for discovering and ranking bimodal signatures from cancer gene expression profiling data | |
Cao et al. | Estimation of tumor cell total mRNA expression in 15 cancer types predicts disease progression | |
JP2021521536A (en) | Machine learning implementation for multi-sample assay of biological samples | |
US20120115138A1 (en) | Method for in vitro diagnosing a complex disease | |
US8030060B2 (en) | Gene signature for diagnosis and prognosis of breast cancer and ovarian cancer | |
Alsaleem et al. | A novel prognostic two-gene signature for triple negative breast cancer | |
Yang et al. | Identification of hub genes and outcome in colon cancer based on bioinformatics analysis | |
Iwamoto et al. | Predicting prognosis of breast cancer with gene signatures: are we lost in a sea of data? | |
Roy et al. | Network information improves cancer outcome prediction | |
Amiri Souri et al. | Cancer Grade Model: a multi-gene machine learning-based risk classification for improving prognosis in breast cancer | |
Pepke et al. | Comprehensive discovery of subsample gene expression components by information explanation: therapeutic implications in cancer | |
Griffith et al. | A robust prognostic signature for hormone-positive node-negative breast cancer | |
Yuan et al. | Prediction of tumor metastasis from sequencing data in the era of genome sequencing | |
Miao et al. | Construction and validation of an RNA-binding protein-associated prognostic model for colorectal cancer | |
Yang et al. | Identification of KIF18B as a hub candidate gene in the metastasis of clear cell renal cell carcinoma by weighted gene co-expression network analysis | |
Zhang et al. | A Novel Immune‐Related Prognostic Signature Predicting Survival in Patients with Pancreatic Adenocarcinoma | |
Zhang et al. | Prognostic value of immune-related lncRNA SBF2-AS1 in diffuse lower-grade glioma | |
Cheng et al. | Computational analysis of mRNA expression profiles identifies a novel triple-biomarker model as prognostic predictor of stage II and III colorectal adenocarcinoma patients | |
García‐Escudero et al. | Gene expression profiling as a tool for basic analysis and clinical application of human cancer | |
Lv et al. | A WGCNA-based cancer-associated fibroblast risk signature in colorectal cancer for prognosis and immunotherapy response |