Research graph
References from Decoding phenotypic screening: A comparative analysis of image representations. Local targets link to admitted publications; unresolved targets remain external evidence.
Annotated high-throughput microscopy image sets for validation
10.1038/nmeth.2083 · 2012 · External reference
Rxrx1: a dataset for evaluating experimental batch correction methods
2023 · External reference
10.1109/cvpr.2009.5206848
10.1109/cvpr.2009.5206848 · External reference
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10.1038/nprot.2016.105
10.1038/nprot.2016.105 · External reference
CellProfiler 4: improvements in speed, utility and usability
10.1186/s12859-021-04344-9 · 2021 · External reference
10.1021/ci100050t
10.1021/ci100050t · External reference
Weakly supervised learning of single-cell feature embeddings
2018 · External reference
A simple framework for contrastive learning of visual representations. In: International conference on machine learning
2020 · External reference
Emerging properties in self-supervised vision transformers
2021 · External reference
CLOOME: contrastive learning unlocks bioimaging databases for queries with chemical structures
10.1038/s41467-023-42328-w · 2023 · External reference
10.1101/085118
10.1101/085118 · External reference
Single-cell phenotype classification using deep convolutional neural networks
10.1177/1087057116631284 · 2016 · External reference
Improving phenotypic measurements in high-content imaging screens
2017 · External reference
10.1177/2472555218818756
10.1177/2472555218818756 · External reference
Accurate prediction of biological assays with high-throughput microscopy images and convolutional networks
10.1021/acs.jcim.8b00670 · 2019 · External reference
Unresolved reference
2022 · External reference
CytoGAN: generative modeling of cell images
2017 · External reference
Capturing single-cell phenotypic variation via unsupervised representation learning
2019 · External reference
Predicting drug polypharmacology from cell morphology readouts using variational autoencoder latent space arithmetic
2022 · External reference
Learning representations for image-based profiling of perturbations
2022 · External reference
Learning unsupervised feature representations for single cell microscopy images with paired cell inpainting
2019 · External reference
Unresolved reference
2022 · External reference
10.1101/2023.06.16.545359
10.1101/2023.06.16.545359 · External reference
10.1101/2023.04.28.538691
10.1101/2023.04.28.538691 · External reference
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10.1126/science.1225829
10.1126/science.1225829 · External reference
10.1016/s1367-5931(00)00110-1
10.1016/s1367-5931(00)00110-1 · External reference
10.1177/108705719700200410
10.1177/108705719700200410 · External reference
A dataset of images and morphological profiles of 30 000 small-molecule treatments using the Cell Painting assay
2017 · External reference
Torchvision the machine-vision package of torch
2010 · External reference
10.1038/s41573-020-00117-w
10.1038/s41573-020-00117-w · External reference
Compound functional prediction using multiple unrelated morphological profiling assays
2017 · External reference
10.1109/cvpr.2016.90
10.1109/cvpr.2016.90 · External reference
10.1038/nmeth.4397
10.1038/nmeth.4397 · External reference
ChEMBL: towards direct deposition of bioassay data
10.1093/nar/gky1075 · 2019 · External reference
Pytorch: an imperative style, high-performance deep learning library
2019 · External reference
10.1093/bioinformatics/btv455
10.1093/bioinformatics/btv455 · External reference
Comparison of the power of the paired samples t test to that of Wilcoxon’s signed-ranks test under various population shapes
10.1037/0033-2909.97.1.119 · 1985 · External reference
Deep-learning: investigating deep neural networks hyper-parameters and comparison of performance to shallow methods for modeling bioactivity data
2017 · External reference
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10.1007/978-3-030-59710-8_14
10.1007/978-3-030-59710-8_14 · External reference
Calculation of the Wasserstein distance between probability distributions on the line
10.1137/1118101 · 1974 · External reference
10.1038/s41592-021-01336-8
10.1038/s41592-021-01336-8 · External reference
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Combining molecular and cell painting image data for mechanism of action prediction
2023 · External reference
