Harrison et al., 2023 - Google Patents
Evaluating the utility of brightfield image data for mechanism of action predictionHarrison et al., 2023
View HTML- Document ID
- 3669818341171848599
- Author
- Harrison P
- Gupta A
- Rietdijk J
- Wieslander H
- Carreras-Puigvert J
- Georgiev P
- Wählby C
- Spjuth O
- Sintorn I
- Publication year
- Publication venue
- PLOS Computational Biology
External Links
Snippet
Fluorescence staining techniques, such as Cell Painting, together with fluorescence microscopy have proven invaluable for visualizing and quantifying the effects that drugs and other perturbations have on cultured cells. However, fluorescence microscopy is expensive …
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
- G01N33/5005—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving human or animal cells
- G01N33/5008—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving human or animal cells for testing or evaluating the effect of chemical or biological compounds, e.g. drugs, cosmetics
- G01N33/502—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving human or animal cells for testing or evaluating the effect of chemical or biological compounds, e.g. drugs, cosmetics for testing non-proliferative effects
-
- 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
- G01N33/68—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving proteins, peptides or amino acids
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30004—Biomedical image processing
- G06T2207/30024—Cell structures in vitro; Tissue sections in vitro
-
- 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
- G06F19/12—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
- G06F19/24—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
- G06F19/28—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
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
-
- 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
- G06K9/00127—Acquiring and recognising microscopic objects, e.g. biological cells and cellular parts
- G06K9/0014—Pre-processing, e.g. image segmentation ; Feature extraction
-
- 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 |
|---|---|---|
| Harrison et al. | Evaluating the utility of brightfield image data for mechanism of action prediction | |
| Wan et al. | Integrating spatial and single-cell transcriptomics data using deep generative models with SpatialScope | |
| Chandrasekaran et al. | Image-based profiling for drug discovery: due for a machine-learning upgrade? | |
| Way et al. | Predicting cell health phenotypes using image-based morphology profiling | |
| Schiff et al. | Integrating deep learning and unbiased automated high-content screening to identify complex disease signatures in human fibroblasts | |
| Lu et al. | Learning unsupervised feature representations for single cell microscopy images with paired cell inpainting | |
| Christiansen et al. | In silico labeling: predicting fluorescent labels in unlabeled images | |
| Caicedo et al. | Data-analysis strategies for image-based cell profiling | |
| Herbert et al. | FindFoci: a focus detection algorithm with automated parameter training that closely matches human assignments, reduces human inconsistencies and increases speed of analysis | |
| US11791019B2 (en) | Systems and methods for high throughput compound library creation | |
| Selinummi et al. | Bright field microscopy as an alternative to whole cell fluorescence in automated analysis of macrophage images | |
| Soelistyo et al. | Learning biophysical determinants of cell fate with deep neural networks | |
| Jammalamadaka et al. | Statistical analysis of dendritic spine distributions in rat hippocampal cultures | |
| Padmanabhan et al. | An active learning approach for rapid characterization of endothelial cells in human tumors | |
| Riordan et al. | Automated analysis and classification of histological tissue features by multi-dimensional microscopic molecular profiling | |
| Danielson et al. | Molecular diversity of glutamatergic and GABAergic synapses from multiplexed fluorescence imaging | |
| Kok et al. | Label-free cell imaging and tracking in 3D organoids | |
| Hagemann et al. | Automated and unbiased discrimination of ALS from control tissue at single cell resolution | |
| Tan et al. | Transfer learning of multicellular organization via single-cell and spatial transcriptomics | |
| Mace et al. | Extraction and comparison of gene expression patterns from 2D RNA in situ hybridization images | |
| Goetz et al. | Current and future use of genomics data in toxicology: opportunities and challenges for regulatory applications | |
| Vulliard et al. | BioProfiling. jl: profiling biological perturbations with high-content imaging in single cells and heterogeneous populations | |
| Zhang et al. | Reference-based cell type matching of spatial transcriptomics data | |
| Zhao et al. | Inferring single-cell spatial gene expression with tissue morphology via explainable deep learning | |
| Savulescu et al. | DypFISH: dynamic patterned FISH to interrogate RNA and protein spatial and temporal subcellular distribution |