ArticleGenome research2004
Automatic identification of subcellular phenotypes on human cell arrays.
Article in Genome research, 2004. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 66 papers.
What it found
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Who cites it
66 citing papers in PubMed, 226 citations in OpenAlex.
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- Shape-to-graph mapping method for efficient characterization and classification of complex geometries in biological images.PLoS computational biology · 2020Article
- Robust classification of cell cycle phase and biological feature extraction by image-based deep learning.Molecular biology of the cell · 2020Article
- A reference library for assigning protein subcellular localizations by image-based machine learning.The Journal of cell biology · 2020Article
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- Multi-parametric characterization of drug effects on cells.F1000Research · 2020Article
- Automated cell boundary and 3D nuclear segmentation of cells in suspension.Scientific reports · 2019Article
- Applying Pattern Recognition to High-Resolution Images to Determine Cellular Signaling Status.IEEE transactions on nanobioscience · 2017Article
- Accurate Classification of Protein Subcellular Localization from High-Throughput Microscopy Images Using Deep Learning.G3 (Bethesda, Md.) · 2017Article
- Machine learning and computer vision approaches for phenotypic profiling.The Journal of cell biology · 2017Review
- High content image analysis of focal adhesion-dependent mechanosensitive stem cell differentiation.Integrative biology : quantitative biosciences from nano to macro · 2016Article
- A High-Throughput Microfluidic Platform for Mammalian Cell Transfection and Culturing.Scientific reports · 2016Article
- Cell-Based Assay Design for High-Content Screening of Drug Candidates.Journal of microbiology and biotechnology · 2016Review
- MIiSR: Molecular Interactions in Super-Resolution Imaging Enables the Analysis of Protein Interactions, Dynamics and Formation of Multi-protein Structures.PLoS computational biology · 2015Article
- The New State of the Art: Cas9 for Gene Activation and Repression.Molecular and cellular biology · 2015Review
- Review
- A systematic comparison of supervised classifiers.PloS one · 2014Article
6 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 3 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Light microscopic analysis of cell morphology provides a high-content readout of cell function and protein localization. Cell arrays and microwell transfection assays on cultured cells have made cell phenotype analysis accessible to high-throughput experiments. Both the localization of each protein in the proteome and the effect of RNAi knock-down of individual genes on cell morphology can be assayed by manual inspection of microscopic images. However, the use of morphological readouts for functional genomics requires fast and automatic identification of complex cellular phenotypes. Here, we present a fully automated platform for high-throughput cell phenotype screening combining human live cell arrays, screening microscopy, and machine-learning-based classification methods. Efficiency of this platform is demonstrated by classification of eleven subcellular patterns marked by GFP-tagged proteins. Our classification method can be adapted to virtually any microscopic assay based on cell morphology, opening a wide range of applications including large-scale RNAi screening in human cells.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.