Nothing Special   »   [go: up one dir, main page]

Madjar, 2018 - Google Patents

Survival models with selection of genomic covariates in heterogeneous cancer studies

Madjar, 2018

View PDF
Document ID
15989056840025895948
Author
Madjar K
Publication year

External Links

Snippet

Survival analysis is an important objective in various fields of biomedical research, particularly in cancer research. Main goals are the prediction of a patient's risk and the identification of new prognostic biomarkers to improve patients' prognosis. In recent years …
Continue reading at eldorado.tu-dortmund.de (PDF) (other versions)

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/10Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology
    • G06F19/24Bioinformatics, 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
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/10Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology
    • G06F19/18Bioinformatics, 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
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/10Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology
    • G06F19/22Bioinformatics, 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
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/10Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology
    • G06F19/28Bioinformatics, 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
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/30Medical informatics, i.e. computer-based analysis or dissemination of patient or disease data
    • G06F19/34Computer-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
    • G06F19/345Medical expert systems, neural networks or other automated diagnosis
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/10Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology
    • G06F19/20Bioinformatics, 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
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/10Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology
    • G06F19/12Bioinformatics, 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
    • CCHEMISTRY; METALLURGY
    • C12BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12QMEASURING 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
    • C12Q1/00Measuring or testing processes involving enzymes, nucleic acids or micro-organisms; Compositions therefor; Processes of preparing such compositions
    • C12Q1/68Measuring or testing processes involving enzymes, nucleic acids or micro-organisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
    • C12Q1/6876Hybridisation probes
    • C12Q1/6883Hybridisation probes for diseases caused by alterations of genetic material
    • C12Q1/6886Hybridisation probes for diseases caused by alterations of genetic material for cancer
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/10Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology
    • G06F19/16Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology for molecular structure, e.g. structure alignment, structural or functional relations, protein folding, domain topologies, drug targeting using structure data, involving two-dimensional or three-dimensional structures
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N99/00Subject matter not provided for in other groups of this subclass
    • G06N99/005Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run

Similar Documents

Publication Publication Date Title
Pal Predictive modeling of drug sensitivity
US20220310199A1 (en) Methods for identifying chromosomal spatial instability such as homologous repair deficiency in low coverage next- generation sequencing data
Albaradei et al. MetaCancer: a deep learning-based pan-cancer metastasis prediction model developed using multi-omics data
CN118773295A (en) Model for targeted sequencing
Lupat et al. Moanna: multi-omics autoencoder-based neural network algorithm for predicting breast cancer subtypes
Liang et al. VSOLassoBag: a variable-selection oriented LASSO bagging algorithm for biomarker discovery in omic-based translational research
Qi et al. Multi-omics data fusion for cancer molecular subtyping using sparse canonical correlation analysis
Wijethilake et al. Survival prediction and risk estimation of Glioma patients using mRNA expressions
Fabregue et al. Mining microarray data to predict the histological grade of a breast cancer
Chen et al. The improvement of breast cancer prognosis accuracy from integrated gene expression and clinical data
Chai et al. Integrating multi-omics data with deep learning for predicting cancer prognosis
Madjar Survival models with selection of genomic covariates in heterogeneous cancer studies
Cambon et al. Classification of clinical outcomes using high-throughput informatics: Part 1–nonparametric method reviews
CN111944902A (en) Early prediction method of renal papillary cell carcinoma based on lincRNA expression profile combination characteristics
Rogan Multigene signatures of responses to chemotherapy derived by biochemically-inspired machine learning
US20230242992A1 (en) Methods of predicting cancer progression
Saha et al. A multiobjective based automatic framework for classifying cancer-microRNA biomarkers
Welsh et al. Bioinformatics analysis to determine prognostic mutations of 72 de novo acute myeloid leukemia cases from the Cancer Genome Atlas (TCGA) with 23 most common mutations and no abnormal cytogenetics
Visakh et al. Multi-network approach to identify differentially methylated gene communities in cancer
Rosenstein et al. Radiogenomics
Menand Machine learning based novel biomarkers discovery for therapeutic use in" pan-gyn" cancers
Esterhuysen Development of a simple artificial intelligence method to accurately subtype breast cancers based on gene expression barcodes
Ow et al. How to discriminate between potentially novel and considered biomarkers within molecular signature?
Kacar Dissecting Tumor Clonality in Liver Cancer: A Phylogeny Analysis Using Computational and Statistical Tools
Mikkonen Modelling the association between cell lines and tumour subtypes in large-scale genomics datasets