CellProfiler 3.0: Next-generation image processing for biology
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CT Rueden, 2017, ImageJ2: ImageJ for the next generation of scientific image data, BMC Bioinformatics, 18, 529, 10.1186/s12859-017-1934-z
A Fillbrunn, 2017, KNIME for reproducible cross-domain analysis of life science data, J Biotechnol, 261, 149, 10.1016/j.jbiotec.2017.07.028
AE Carpenter, 2006, CellProfiler: image analysis software for identifying and quantifying cell phenotypes, Genome Biol, 7, R100, 10.1186/gb-2006-7-10-r100
L Kamentsky, 2011, Improved structure, function and compatibility for CellProfiler: modular high-throughput image analysis software, Bioinformatics, 27, 1179, 10.1093/bioinformatics/btr095
V Wiesmann, 2015, Review of free software tools for image analysis of fluorescence cell micrographs, J Microsc, 257, 39, 10.1111/jmi.12184
A Bray M-, 2016, Cell Painting, a high-content image-based assay for morphological profiling using multiplexed fluorescent dyes, Nat Protoc, 11, 1757, 10.1038/nprot.2016.105
MH Rohban, 2017, Systematic morphological profiling of human gene and allele function via Cell Painting, Elife, 6, 10.7554/eLife.24060
JC Caicedo, 2016, Applications in image-based profiling of perturbations, Curr Opin Biotechnol, 39, 134, 10.1016/j.copbio.2016.04.003
F Long, 2012, Visualization and Analysis of 3D Microscopic Images, PLoS Comput Biol, 8, e1002519, 10.1371/journal.pcbi.1002519
D Svoboda, 2017, MitoGen: A Framework for Generating 3D Synthetic Time-Lapse Sequences of Cell Populations in Fluorescence Microscopy, IEEE Trans Med Imaging, 36, 310, 10.1109/TMI.2016.2606545
D Svoboda, 2009, Generation of digital phantoms of cell nuclei and simulation of image formation in 3D image cytometry, Cytometry A, 75, 494, 10.1002/cyto.a.20714
WM Rand, 1971, Objective Criteria for the Evaluation of Clustering Methods, J Am Stat Assoc, 66, 846, 10.1080/01621459.1971.10482356
V Ulman, 2017, An objective comparison of cell-tracking algorithms, Nat Methods, 14, 1141, 10.1038/nmeth.4473
V Ljosa, 2012, Annotated high-throughput microscopy image sets for validation, Nat Methods, 9, 637, 10.1038/nmeth.2083
A Krizhevsky, 2012, Advances in Neural Information Processing Systems 25, 1097
O Ronneberger, 2015, U-Net: Convolutional Networks for Biomedical Image Segmentation, Medical Image Computing and Computer-Assisted Intervention–MICCAI 2015, 234, 10.1007/978-3-319-24574-4_28
M Abadi, 2016, TensorFlow: A System for Large-Scale Machine Learning, OSDI, 265
Jia Y, Shelhamer E, Donahue J, Karayev S, Long J, Girshick R, et al. Caffe: Convolutional Architecture for Fast Feature Embedding. Proceedings of the 22Nd ACM International Conference on Multimedia. New York, NY, USA: ACM; 2014. pp. 675–678.
SJ Yang, 2018, Assessing microscope image focus quality with deep learning, BMC Bioinformatics, 19, 28962
SK Sadanandan, 2017, Automated Training of Deep Convolutional Neural Networks for Cell Segmentation, Sci Rep, 7, 7860, 10.1038/s41598-017-07599-6
Y Sakurai, 2015, Ebola virus. Two-pore channels control Ebola virus host cell entry and are drug targets for disease treatment, Science, 347, 995, 10.1126/science.1258758
SA Stanley, 2014, Identification of host-targeted small molecules that restrict intracellular Mycobacterium tuberculosis growth, PLoS Pathog, 10, e1003946, 10.1371/journal.ppat.1003946
Q Wen, 2012, Identification of regulators of polyploidization presents therapeutic targets for treatment of AMKL, Cell, 150, 575, 10.1016/j.cell.2012.06.032
KA Hartwell, 2013, Niche-based screening identifies small-molecule inhibitors of leukemia stem cells, Nat Chem Biol, 9, 840, 10.1038/nchembio.1367
CC Gibson, 2015, Strategy for identifying repurposed drugs for the treatment of cerebral cavernous malformation, Circulation, 131, 289, 10.1161/CIRCULATIONAHA.114.010403
B Snijder, 2017, Image-based ex-vivo drug screening for patients with aggressive haematological malignancies: interim results from a single-arm, open-label, pilot study, Lancet Haematol, 4, e595, 10.1016/S2352-3026(17)30208-9
E Pennisi, 2016, IMAGING. “Cell painting” highlights responses to drugs and toxins, Science, 352, 877, 10.1126/science.352.6288.877
JC Caicedo, 2017, Data-analysis strategies for image-based cell profiling, Nat Methods, 14, 849, 10.1038/nmeth.4397
D Dao, 2016, CellProfiler Analyst: interactive data exploration, analysis and classification of large biological image sets, Bioinformatics
T Ching, 2017, Opportunities And Obstacles For Deep Learning In Biology And Medicine, bioRxiv, 142760
NC Rivron, 2018, Blastocyst-like structures generated solely from stem cells, Nature, 557, 106, 10.1038/s41586-018-0051-0