Walther et al., 2009 - Google Patents
Automatic clustering of flow cytometry data with density‐based mergingWalther et al., 2009
View PDF- Document ID
- 15470936146703963026
- Author
- Walther G
- Zimmerman N
- Moore W
- Parks D
- Meehan S
- Belitskaya I
- Pan J
- Herzenberg L
- Publication year
- Publication venue
- Advances in bioinformatics
External Links
Snippet
The ability of flow cytometry to allow fast single cell interrogation of a large number of cells has made this technology ubiquitous and indispensable in the clinical and laboratory setting. A current limit to the potential of this technology is the lack of automated tools for …
- 238000000684 flow cytometry 0 title abstract description 14
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
- G06F17/30286—Information retrieval; Database structures therefor; File system structures therefor in structured data stores
- G06F17/30587—Details of specialised database models
-
- 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
- G06F19/20—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
- 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
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management, e.g. organising, planning, scheduling or allocating time, human or machine resources; Enterprise planning; Organisational models
-
- 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
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N99/00—Subject matter not provided for in other groups of this subclass
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Greenwald et al. | Whole-cell segmentation of tissue images with human-level performance using large-scale data annotation and deep learning | |
Quintelier et al. | Analyzing high-dimensional cytometry data using FlowSOM | |
Walther et al. | Automatic clustering of flow cytometry data with density‐based merging | |
Chen et al. | Single-cell trajectories reconstruction, exploration and mapping of omics data with STREAM | |
Höllt et al. | Cytosplore: interactive immune cell phenotyping for large single‐cell datasets | |
Walker et al. | Deciphering tissue structure and function using spatial transcriptomics | |
US10289802B2 (en) | Spanning-tree progression analysis of density-normalized events (SPADE) | |
CN108198621B (en) | Database data comprehensive diagnosis and treatment decision method based on neural network | |
O'Neill et al. | Flow cytometry bioinformatics | |
Qiu et al. | Extracting a cellular hierarchy from high-dimensional cytometry data with SPADE | |
CN113454733A (en) | Multi-instance learner for prognostic tissue pattern recognition | |
Kraus et al. | Computer vision for high content screening | |
Saez-Rodriguez et al. | Flexible informatics for linking experimental data to mathematical models via DataRail | |
CN107391963A (en) | Eucaryon based on calculating cloud platform is without ginseng transcript profile interaction analysis system and method | |
Stöter et al. | CellProfiler and KNIME: open source tools for high content screening | |
Chessel et al. | From observing to predicting single-cell structure and function with high-throughput/high-content microscopy | |
CN108206056B (en) | Nasopharyngeal darcinoma artificial intelligence assists diagnosis and treatment decision-making terminal | |
Chang et al. | Crowdsourced geometric morphometrics enable rapid large-scale collection and analysis of phenotypic data | |
Pretorius et al. | A survey of visualization for live cell imaging | |
Zhao et al. | Intelligent upgrading of plant breeding: Decision support tools in the golden seed breeding cloud platform | |
Pan et al. | LinRace: cell division history reconstruction of single cells using paired lineage barcode and gene expression data | |
Folcarelli et al. | Automated flow cytometric identification of disease-specific cells by the ECLIPSE algorithm | |
CN108320797B (en) | Nasopharyngeal carcinoma database and comprehensive diagnosis and treatment decision method based on database | |
Subrahmanya et al. | Advanced machine learning methods for production data pattern recognition | |
Schraivogel et al. | Cell sorters see things more clearly now |