| scholarly article | Q13442814 |
| P6179 | Dimensions Publication ID | 1091400545 |
| P356 | DOI | 10.1038/NMETH.4397 |
| P932 | PMC publication ID | 6871000 |
| P698 | PubMed publication ID | 28858338 |
| P50 | author | Roger G Linington | Q41365997 |
| Anne E Carpenter | Q50597627 | ||
| Paul Rees | Q55979455 | ||
| Florian Heigwer | Q55979676 | ||
| Scott Warchal | Q55979683 | ||
| Joseph D Barry | Q55979684 | ||
| Holger Hennig | Q57630910 | ||
| P2093 | author name string | Ian Smith | |
| Peter Horvath | |||
| Sam Cooper | |||
| Paul A Clemons | |||
| Mathias Wawer | |||
| Lassi Paavolainen | |||
| Shantanu Singh | |||
| Peng Qiu | |||
| Csaba Molnar | |||
| Juan C Caicedo | |||
| Markus D Herrmann | |||
| John Concannon | |||
| Jane Hung | |||
| Aliaksei S Vasilevich | |||
| Mohammad Rohban | |||
| Harmanjit Singh Bansal | |||
| Oren Kraus | |||
| P2860 | cites work | Annotated high-throughput microscopy image sets for validation | Q39870104 |
| Quantitative morphological signatures define local signaling networks regulating cell morphology. | Q40115889 | ||
| Analysis of high-throughput screening reveals the effect of surface topographies on cellular morphology. | Q41632326 | ||
| Positional artifacts in microarrays: experimental verification and construction of COP, an automated detection tool | Q41824247 | ||
| Clustering phenotype populations by genome-wide RNAi and multiparametric imaging. | Q42049385 | ||
| Classifying and segmenting microscopy images with deep multiple instance learning | Q42107285 | ||
| A chemical-genetic interaction map of small molecules using high-throughput imaging in cancer cells. | Q42675375 | ||
| The multidimensional perturbation value: a single metric to measure similarity and activity of treatments in high-throughput multidimensional screens | Q44071271 | ||
| A simple technique for reducing edge effect in cell-based assays | Q44624289 | ||
| Machine Learning Improves the Precision and Robustness of High-Content Screens: Using Nonlinear Multiparametric Methods to Analyze Screening Results | Q45961679 | ||
| A cell profiling framework for modeling drug responses from HCS imaging | Q46821003 | ||
| A global geometric framework for nonlinear dimensionality reduction | Q47014659 | ||
| CIDRE: an illumination-correction method for optical microscopy | Q48216198 | ||
| An efficient method for the detection and elimination of systematic error in high-throughput screening | Q48403578 | ||
| IMAGING. 'Cell painting' highlights responses to drugs and toxins | Q48614604 | ||
| Data reduction for spectral clustering to analyze high throughput flow cytometry data | Q21284349 | ||
| NIH Image to ImageJ: 25 years of image analysis | Q23319322 | ||
| Single-cell mass cytometry of differential immune and drug responses across a human hematopoietic continuum | Q24594356 | ||
| Statistical methods for analysis of high-throughput RNA interference screens | Q24644919 | ||
| WND-CHARM: Multi-purpose image classification using compound image transforms | Q24647960 | ||
| CellProfiler: image analysis software for identifying and quantifying cell phenotypes | Q24676898 | ||
| A functional genomic analysis of cell morphology using RNA interference | Q24794931 | ||
| Relationship between gene co-expression and probe localization on microarray slides | Q24804774 | ||
| Applications in image-based profiling of perturbations | Q26752791 | ||
| Apolar and polar transitions drive the conversion between amoeboid and mesenchymal shapes in melanoma cells. | Q27305381 | ||
| A comparison of normalization methods for high density oligonucleotide array data based on variance and bias | Q27860710 | ||
| The case for open computer programs | Q27921796 | ||
| Deep learning | Q28018765 | ||
| Visualizing quantitative microscopy data: History and challenges | Q28066243 | ||
| Pipeline for illumination correction of images for high-throughput microscopy | Q28248105 | ||
| OMERO: flexible, model-driven data management for experimental biology | Q28260901 | ||
| Computer vision for image-based transcriptomics. | Q50908121 | ||
| Multidimensional drug profiling by automated microscopy | Q51984398 | ||
| A feature set for cytometry on digitized microscopic images | Q52022389 | ||
| A comparison of different focus functions for use in autofocus algorithms | Q52674915 | ||
| Mapping genetic interactions in human cancer cells with RNAi and multiparametric phenotyping. | Q53112710 | ||
| Linking phenotypes and modes of action through high-content screen fingerprints. | Q54253745 | ||
| Gene Selection for Cancer Classification using Support Vector Machines | Q56535529 | ||
| A Grand Challenge. 2. Phenotypic Profiling of a Natural Product Library on Parkinson’s Patient-Derived Cells | Q56986969 | ||
| Distributed online anomaly detection in high-content screening | Q57392804 | ||
| A brain tumor segmentation framework based on outlier detection*1 | Q57512209 | ||
| Ilastik: Interactive learning and segmentation toolkit | Q59759014 | ||
| A Hierarchical Map of Regulatory Genetic Interactions in Membrane Trafficking | Q60571744 | ||
| Texture discrimination by Gabor functions | Q69715530 | ||
| Retrospective shading correction based on entropy minimization | Q73486714 | ||
| Visual sensitivity, blur and the sources of variability in the amplitude spectra of natural scenes | Q74025736 | ||
| Image-based multivariate profiling of drug responses from single cells | Q80078371 | ||
| Comparison of quantitative methods for cell-shape analysis | Q81227498 | ||
| Origins of regulated cell-to-cell variability | Q83171482 | ||
| Genome-wide RNAi Screening Identifies Protein Modules Required for 40S Subunit Synthesis in Human Cells | Q86985379 | ||
| Systematic morphological profiling of human gene and allele function via Cell Painting. | Q37745645 | ||
| Single-cell and multivariate approaches in genetic perturbation screens | Q38274975 | ||
| Microscopy-Based High-Content Screening. | Q38659736 | ||
| Computer vision for high content screening | Q38710186 | ||
| High-Content Screening for Quantitative Cell Biology. | Q38818760 | ||
| Accurate Classification of Protein Subcellular Localization from High-Throughput Microscopy Images Using Deep Learning | Q38846118 | ||
| Large-scale image-based screening and profiling of cellular phenotypes. | Q38902128 | ||
| A multi-scale convolutional neural network for phenotyping high-content cellular images | Q38958887 | ||
| Effect-Size Measures as Descriptors of Assay Quality in High-Content Screening: A Brief Review of Some Available Methodologies | Q38992715 | ||
| Machine learning and computer vision approaches for phenotypic profiling | Q39035630 | ||
| Benchmarking of multivariate similarity measures for high-content screening fingerprints in phenotypic drug discovery | Q39094539 | ||
| High-content phenotypic profiling of drug response signatures across distinct cancer cells | Q39695815 | ||
| Integration of multiple readouts into the z' factor for assay quality assessment | Q39770488 | ||
| EBImage--an R package for image processing with applications to cellular phenotypes. | Q39783161 | ||
| Population context determines cell-to-cell variability in endocytosis and virus infection | Q39807636 | ||
| Target identification by image analysis | Q28272139 | ||
| A chemical screen probing the relationship between mitochondrial content and cell size | Q28481860 | ||
| Multiplex cytological profiling assay to measure diverse cellular states | Q28535626 | ||
| openBIS: a flexible framework for managing and analyzing complex data in biology research | Q28732175 | ||
| Improving drug discovery with high-content phenotypic screens by systematic selection of reporter cell lines | Q28834223 | ||
| Interactive notebooks: Sharing the code | Q28851715 | ||
| Reproducibility of computational workflows is automated using continuous analysis | Q28950439 | ||
| Variance stabilization applied to microarray data calibration and to the quantification of differential expression | Q29614492 | ||
| Phenotypic profiling of the human genome by time-lapse microscopy reveals cell division genes | Q29615188 | ||
| Tackling the widespread and critical impact of batch effects in high-throughput data | Q30004214 | ||
| Scoring diverse cellular morphologies in image-based screens with iterative feedback and machine learning | Q30485759 | ||
| Cross-talk between Rho and Rac GTPases drives deterministic exploration of cellular shape space and morphological heterogeneity. | Q30570343 | ||
| viSNE enables visualization of high dimensional single-cell data and reveals phenotypic heterogeneity of leukemia | Q30628090 | ||
| A variance-stabilizing transformation for gene-expression microarray data | Q30712210 | ||
| Data Acquisition and Preprocessing in Studies on Humans: What Is Not Taught in Statistics Classes? | Q30753296 | ||
| Rapid Assessment and Visualization of Normality in High-Content and Other Cell-Level Data and Its Impact on the Interpretation of Experimental Results | Q30782490 | ||
| Diffusion maps for high-dimensional single-cell analysis of differentiation data. | Q30957322 | ||
| Impact of normalization methods on high-throughput screening data with high hit rates and drug testing with dose-response data | Q30985881 | ||
| Minimum redundancy feature selection from microarray gene expression data | Q30988046 | ||
| Statistical practice in high-throughput screening data analysis | Q31032001 | ||
| Visualization and cellular hierarchy inference of single-cell data using SPADE. | Q31108504 | ||
| CellProfiler Analyst: interactive data exploration, analysis and classification of large biological image sets | Q31111225 | ||
| Automated recognition of patterns characteristic of subcellular structures in fluorescence microscopy images | Q31971753 | ||
| Genome-wide functional analysis of human cell-cycle regulators. | Q33258371 | ||
| Compound classification using image-based cellular phenotypes | Q33263842 | ||
| Integrating high-content screening and ligand-target prediction to identify mechanism of action | Q33309163 | ||
| CellProfiler Analyst: data exploration and analysis software for complex image-based screens | Q33384957 | ||
| CellClassifier: supervised learning of cellular phenotypes | Q33499940 | ||
| Automated analysis of high-content microscopy data with deep learning | Q33613705 | ||
| Discovering biological progression underlying microarray samples | Q33886691 | ||
| Patterns of basal signaling heterogeneity can distinguish cellular populations with different drug sensitivities | Q33932561 | ||
| Evaluation of three methods for retrospective correction of vignetting on medical microscopy images utilizing two open source software tools | Q34032243 | ||
| Extracting a cellular hierarchy from high-dimensional cytometry data with SPADE | Q34037159 | ||
| Cellular heterogeneity: do differences make a difference? | Q34052445 | ||
| Judging the quality of gene expression-based clustering methods using gene annotation | Q34153265 | ||
| Single-cell analysis of population context advances RNAi screening at multiple levels | Q34244392 | ||
| Improved statistical methods for hit selection in high-throughput screening | Q34288539 | ||
| A map of directional genetic interactions in a metazoan cell | Q34466080 | ||
| Increasing the Content of High-Content Screening: An Overview | Q34505840 | ||
| "Function-first" lead discovery: mode of action profiling of natural product libraries using image-based screening | Q34601049 | ||
| Determining the subcellular location of new proteins from microscope images using local features | Q34803023 | ||
| From cellular characteristics to disease diagnosis: uncovering phenotypes with supercells | Q34987982 | ||
| Comparison of methods for image-based profiling of cellular morphological responses to small-molecule treatment | Q34991555 | ||
| Large-scale cytological profiling for functional analysis of bioactive compounds. | Q34993832 | ||
| A novel phenotypic dissimilarity method for image-based high-throughput screens. | Q35047527 | ||
| The Image Data Resource: A Bioimage Data Integration and Publication Platform | Q35065468 | ||
| Cell shape and the microenvironment regulate nuclear translocation of NF-κB in breast epithelial and tumor cells | Q35236726 | ||
| Rapid analysis and exploration of fluorescence microscopy images. | Q35326063 | ||
| Removing batch effects from purified plasma cell gene expression microarrays with modified ComBat | Q35607341 | ||
| Morphological Profiles of RNAi-Induced Gene Knockdown Are Highly Reproducible but Dominated by Seed Effects | Q35702911 | ||
| High-Content Analysis of Breast Cancer Using Single-Cell Deep Transfer Learning | Q35889085 | ||
| CP-CHARM: segmentation-free image classification made accessible | Q35905946 | ||
| Cell Painting, a high-content image-based assay for morphological profiling using multiplexed fluorescent dyes. | Q36112726 | ||
| Deep Learning Automates the Quantitative Analysis of Individual Cells in Live-Cell Imaging Experiments | Q36182843 | ||
| Correcting positional correlations in Affymetrix® genome chips | Q36292049 | ||
| Workflow and metrics for image quality control in large-scale high-content screens | Q36671239 | ||
| Wndchrm - an open source utility for biological image analysis | Q36782372 | ||
| A call for bioimaging software usability | Q36810395 | ||
| Biological imaging software tools | Q36861970 | ||
| The cellular microscopy phenotype ontology | Q36911177 | ||
| Innovation in academic chemical screening: filling the gaps in chemical biology | Q37037229 | ||
| Accurate Morphology Preserving Segmentation of Overlapping Cells based on Active Contours | Q37211051 | ||
| Time series modeling of live-cell shape dynamics for image-based phenotypic profiling | Q37327840 | ||
| PhenoRipper: software for rapidly profiling microscopy images | Q37347499 | ||
| Multi-parameter phenotypic profiling: using cellular effects to characterize small-molecule compounds | Q37536897 | ||
| P275 | copyright license | Creative Commons Attribution 4.0 International | Q20007257 |
| P6216 | copyright status | copyrighted | Q50423863 |
| P4510 | describes a project that uses | Jupyter notebook file | Q70357595 |
| P433 | issue | 9 | |
| P921 | main subject | data analysis | Q1988917 |
| P304 | page(s) | 849-863 | |
| P577 | publication date | 2017-08-01 | |
| P1433 | published in | Nature Methods | Q680640 |
| P1476 | title | Data-analysis strategies for image-based cell profiling | |
| P478 | volume | 14 |
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