Yang et al., 2023 - Google Patents
Pan-cancer evolution signatures link clonal expansion to dynamic changes in the tumour immune microenvironmentYang et al., 2023
View PDF- Document ID
- 17515159474358135578
- Author
- Yang X
- Liu W
- Macintyre G
- Van Loo P
- Markowetz F
- Bailey P
- Yuan K
- Publication year
- Publication venue
- bioRxiv
External Links
Snippet
Cancer is an evolutionary process characterised by profound intra-tumour heterogeneity. Intra-tumour heterogeneity can be quantified using in silico estimates of cancer cell fractions of tumour-specific somatic mutations. Here we demonstrate a data-driven approach that …
Classifications
-
- 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
- G06F19/18—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
- G06F19/12—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
- G06F19/10—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
- G06F19/30—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
- 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
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Lazar et al. | Comprehensive and integrated genomic characterization of adult soft tissue sarcomas | |
JP7545891B2 (en) | Systems and methods for analyzing mixed cell populations - Patents.com | |
CN109689891B (en) | Methods for fragment profiling of cell-free nucleic acids | |
Taylor et al. | Functional copy-number alterations in cancer | |
Park et al. | Subtype-specific signaling pathways and genomic aberrations associated with prognosis of glioblastoma | |
Wang et al. | Predicting molecular phenotypes from histopathology images: a transcriptome-wide expression–morphology analysis in breast cancer | |
Haibe-Kains et al. | A three-gene model to robustly identify breast cancer molecular subtypes | |
Leshchiner et al. | Comprehensive analysis of tumour initiation, spatial and temporal progression under multiple lines of treatment | |
Kalender Atak et al. | High accuracy mutation detection in leukemia on a selected panel of cancer genes | |
Cheng et al. | A mathematical methodology for determining the temporal order of pathway alterations arising during gliomagenesis | |
Armstrong et al. | Microarray data analysis: from hypotheses to conclusions using gene expression data | |
Long et al. | A mutation-based gene set predicts survival benefit after immunotherapy across multiple cancers and reveals the immune response landscape | |
Alkallas et al. | Multi-omic analysis reveals significantly mutated genes and DDX3X as a sex-specific tumor suppressor in cutaneous melanoma | |
Garrett-Mayer et al. | Cross-study validation and combined analysis of gene expression microarray data | |
Letouzé et al. | Analysis of the copy number profiles of several tumor samples from the same patient reveals the successive steps in tumorigenesis | |
Walter et al. | Clinical application of whole transcriptome sequencing for the classification of patients with acute lymphoblastic leukemia | |
Qin et al. | Deconvolution of heterogeneous tumor samples using partial reference signals | |
Zhang et al. | Sources of variation in false discovery rate estimation include sample size, correlation, and inherent differences between groups | |
Lucas et al. | A Bayesian analysis strategy for cross-study translation of gene expression biomarkers | |
Wang et al. | Genetic intratumor heterogeneity remodels the immune microenvironment and induces immune evasion in brain metastasis of lung cancer | |
Yang et al. | Pan-cancer evolution signatures link clonal expansion to dynamic changes in the tumour immune microenvironment | |
Burr et al. | Developmental mosaicism underlying EGFR-mutant lung cancer presenting with multiple primary tumors | |
Tabak et al. | The Tangent copy-number inference pipeline for cancer genome analyses | |
Li et al. | Gene co-expression modules integrated with immunoscore predicts survival of non-small cell lung cancer | |
Sanghvi et al. | Charting the transcriptomic landscape of primary and metastatic cancers in relation to their origin and target normal tissues |