Weinstein et al., 2019 - Google Patents
DNA microscopy: optics-free spatio-genetic imaging by a stand-alone chemical reactionWeinstein et al., 2019
View HTML- Document ID
- 14588141694821702287
- Author
- Weinstein J
- Regev A
- Zhang F
- Publication year
- Publication venue
- Cell
External Links
Snippet
Analyzing the spatial organization of molecules in cells and tissues is a cornerstone of biological research and clinical practice. However, despite enormous progress in molecular profiling of cellular constituents, spatially mapping them remains a disjointed and …
- 229920003013 deoxyribonucleic acid 0 title abstract description 108
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
- G06F19/20—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
- 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
- G06F19/18—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
- 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
-
- 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
- C12Q1/6813—Hybridisation assays
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/62—Methods or arrangements for recognition using electronic means
- G06K9/6217—Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Weinstein et al. | DNA microscopy: optics-free spatio-genetic imaging by a stand-alone chemical reaction | |
Hwang et al. | Single-cell RNA sequencing technologies and bioinformatics pipelines | |
Kiselev et al. | Challenges in unsupervised clustering of single-cell RNA-seq data | |
Gomes et al. | Immunology driven by large-scale single-cell sequencing | |
EP3520006B1 (en) | Phenotype/disease specific gene ranking using curated, gene library and network based data structures | |
Brentani et al. | Gene expression arrays in cancer research: methods and applications | |
US10281456B1 (en) | Systems and methods for discriminating effects on targets | |
Crow et al. | Co-expression in single-cell analysis: saving grace or original sin? | |
NL2023311B1 (en) | Artificial intelligence-based generation of sequencing metadata | |
EP3881328A1 (en) | Systems and methods for high throughput compound library creation | |
Sankowski et al. | Evaluating microglial phenotypes using single-cell technologies | |
Wolfien et al. | Single-cell RNA sequencing procedures and data analysis | |
Hartman et al. | Comparative analysis of multiplexed in situ gene expression profiling technologies | |
Deng et al. | Microtechnologies for single-cell and spatial multi-omics | |
Wang et al. | Integration of computational analysis and spatial transcriptomics in single-cell studies | |
Roberts et al. | Transcriptome-wide spatial RNA profiling maps the cellular architecture of the developing human neocortex | |
Heydari et al. | Deep learning in spatial transcriptomics: Learning from the next next-generation sequencing | |
Dasgupta et al. | Single-cell RNA sequencing: a new window into cell scale dynamics | |
Zhang et al. | Reference-based cell type matching of spatial transcriptomics data | |
Crow et al. | Single cell RNA-sequencing: replicability of cell types | |
Deepa et al. | Development of a Fully Automated Image Analysis Method for High Density cDNA and array CGH Microarray Based Genomic Studies | |
Koo et al. | Interpreting deep neural networks beyond attribution methods: quantifying global importance of genomic features | |
Tan et al. | Current and future perspectives of single-cell multi-omics technologies in cardiovascular research | |
Koch et al. | CLIMB: High-dimensional association detection in large scale genomic data | |
Li et al. | Analysis and Visualization of Single-Cell Sequencing Data with Scanpy and MetaCell: A Tutorial |