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Building a 3D Integrated Cell

https://doi.org/10.1101/238378
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1002/cyto.a.20487openalex-snapshot
Automated learning of generative models for subcellular location: Building blocks for systems biology
inferredcites →https://doi.org/10.1002/cyto.a.21066openalex-snapshot
Image‐derived, three‐dimensional generative models of cellular organization
inferredcites →https://doi.org/10.1017/9781108891530.013openalex-snapshot
Generative Adversarial Networks
inferredcites →https://doi.org/10.1038/nature13302openalex-snapshot
A draft map of the human proteome
inferredcites →https://doi.org/10.1038/nbt1228openalex-snapshot
Global mapping of pharmacological space
inferredcites →https://doi.org/10.1038/nmeth.2097openalex-snapshot
PhenoRipper: software for rapidly profiling microscopy images
inferredcites →https://doi.org/10.1042/bst0330535openalex-snapshot
Location proteomics: a systems approach to subcellular location
inferredcites →https://doi.org/10.1091/mbc.e15-06-0370openalex-snapshot
Joint modeling of cell and nuclear shape variation
inferredcites →https://doi.org/10.1093/bioinformatics/17.12.1213openalex-snapshot
A neural network classifier capable of recognizing the patterns of all major subcellular structures in fluorescence microscope images of HeLa cells
inferredcites →https://doi.org/10.1101/227645openalex-snapshot
CytoGAN: Generative Modeling of Cell Images
inferredcites →https://doi.org/10.1186/gb-2006-7-10-r100openalex-snapshot
CellProfiler: image analysis software for identifying and quantifying cell phenotypes
inferredcites →https://doi.org/10.1371/journal.pcbi.1004611openalex-snapshot
Unbiased Rare Event Sampling in Spatial Stochastic Systems Biology Models Using a Weighted Ensemble of Trajectories
inferredcites →https://doi.org/10.48550/arxiv.1511.06434openalex-snapshot
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
inferredcites →https://doi.org/10.48550/arxiv.1606.03498openalex-snapshot
Improved Techniques for Training GANs
inferredcites →https://doi.org/10.48550/arxiv.1610.04490openalex-snapshot
Amortised MAP Inference for Image Super-resolution
inferredcites →https://doi.org/10.48550/arxiv.1705.00092openalex-snapshot
Generative Modeling with Conditional Autoencoders: Building an Integrated Cell
inferredcites →https://doi.org/10.7554/elife.10047openalex-snapshot
Active machine learning-driven experimentation to determine compound effects on protein patterns

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1007/978-3-030-01388-2_10openalex-snapshot
Immersive Analytics Applications in Life and Health Sciences
inferred← citeshttps://doi.org/10.1007/978-3-030-87237-3_46openalex-snapshot
Multi-StyleGAN: Towards Image-Based Simulation of Time-Lapse Live-Cell Microscopy
inferred← citeshttps://doi.org/10.1007/s12021-021-09536-5openalex-snapshot
High-throughput Analysis of Synaptic Activity in Electrically Stimulated Neuronal Cultures
inferred← citeshttps://doi.org/10.1016/b978-0-12-824349-7.00028-1openalex-snapshot
Review of cell image synthesis for image processing
inferred← citeshttps://doi.org/10.1016/j.cels.2021.05.003openalex-snapshot
Interpretable deep learning uncovers cellular properties in label-free live cell images that are predictive of highly metastatic melanoma
inferred← citeshttps://doi.org/10.1016/j.displa.2026.103426openalex-snapshot
Diffusion-based generation of cell images with quantitative fluorescence for precise and interpretable protein subcellular localization
inferred← citeshttps://doi.org/10.1016/j.micron.2022.103302openalex-snapshot
Discrete Protein Metric (DPM): A new image similarity metric to calculate accuracy of deep learning-generated cell focal adhesion predictions
inferred← citeshttps://doi.org/10.1017/s2633903x23000193openalex-snapshot
Annotation-free learning of a spatio-temporal manifold of the cell life cycle
inferred← citeshttps://doi.org/10.1038/s41467-021-26577-1openalex-snapshot
Physics-informed deep learning characterizes morphodynamics of Asian soybean rust disease
inferred← citeshttps://doi.org/10.1038/s41467-024-45362-4openalex-snapshot
Orientation-invariant autoencoders learn robust representations for shape profiling of cells and organelles
inferred← citeshttps://doi.org/10.1038/s41592-019-0403-1openalex-snapshot
Deep learning for cellular image analysis
inferred← citeshttps://doi.org/10.1038/s41592-019-0458-zopenalex-snapshot
Applications, promises, and pitfalls of deep learning for fluorescence image reconstruction
inferred← citeshttps://doi.org/10.1038/s41596-020-00432-xopenalex-snapshot
A robust unsupervised machine-learning method to quantify the morphological heterogeneity of cells and nuclei
inferred← citeshttps://doi.org/10.1038/s41598-023-45150-yopenalex-snapshot
Virtual staining for pixel-wise and quantitative analysis of single cell images
inferred← citeshttps://doi.org/10.1038/s41598-026-44976-6openalex-snapshot
A diffusion model conditioned on compound bioactivity profiles for generating high-content images
inferred← citeshttps://doi.org/10.1038/s42256-020-00283-xopenalex-snapshot
Global voxel transformer networks for augmented microscopy
inferred← citeshttps://doi.org/10.1098/rsif.2017.0387openalex-snapshot
Opportunities and obstacles for deep learning in biology and medicine
inferred← citeshttps://doi.org/10.1098/rstb.2021.0469openalex-snapshot
CardioVinci: building blocks for virtual cardiac cells using deep learning
inferred← citeshttps://doi.org/10.1101/2020.10.27.358101openalex-snapshot
Counterfactual Hypothesis Testing of Tumor Microenvironment Scenarios Through Semantic Image Synthesis
inferred← citeshttps://doi.org/10.1101/2021.08.22.457257openalex-snapshot
CardioVinci: building blocks for virtual cardiac cells using deep learning
inferred← citeshttps://doi.org/10.1101/2022.11.12.516283openalex-snapshot
Using conditional Generative Adversarial Networks (GAN) to generate de novo synthetic cell nuclei for training machine learning-based image segmentation
inferred← citeshttps://doi.org/10.1101/2022.12.08.519671openalex-snapshot
Learning orientation-invariant representations enables accurate and robust morphologic profiling of cells and organelles
inferred← citeshttps://doi.org/10.1101/2024.10.10.616543openalex-snapshot
A diffusion model conditioned on compound bioactivity profiles for predicting high-content images
inferred← citeshttps://doi.org/10.1101/433763openalex-snapshot
Unsupervised deep learning with variational autoencoders applied to breast tumor genome-wide DNA methylation data with biologic feature extraction
inferred← citeshttps://doi.org/10.1371/journal.pcbi.1007348openalex-snapshot
Learning unsupervised feature representations for single cell microscopy images with paired cell inpainting
inferred← citeshttps://doi.org/10.1371/journal.pcbi.1007717openalex-snapshot
An in-silico human cell model reveals the influence of spatial organization on RNA splicing
inferred← citeshttps://doi.org/10.1371/journal.pcbi.1009155openalex-snapshot
A deep generative model of 3D single-cell organization
inferred← citeshttps://doi.org/10.1371/journal.pone.0258546openalex-snapshot
Learning to see colours: Biologically relevant virtual staining for adipocyte cell images
inferred← citeshttps://doi.org/10.1371/journal.pone.0265567openalex-snapshot
Auto-segmentation and time-dependent systematic analysis of mesoscale cellular structure in β-cells during insulin secretion
inferred← citeshttps://doi.org/10.14740/cr1179openalex-snapshot
Heart, Eye, and Artificial Intelligence: A Review
inferred← citeshttps://doi.org/10.31219/osf.io/axy82openalex-snapshot
Cell2Cell: Explorative Cell Interaction Analysis in Multi-Volumetric Tissue Data
inferred← citeshttps://doi.org/10.3389/fbioe.2019.00443openalex-snapshot
Engineering Tissue Fabrication With Machine Intelligence: Generating a Blueprint for Regeneration
inferred← citeshttps://doi.org/10.3389/fcomp.2019.00010openalex-snapshot
Generative Adversarial Networks for Augmenting Training Data of Microscopic Cell Images
inferred← citeshttps://doi.org/10.3389/fphy.2019.00247openalex-snapshot
Applications and Challenges of Machine Learning to Enable Realistic Cellular Simulations
inferred← citeshttps://doi.org/10.7554/elife.55913openalex-snapshot
An image-based data-driven analysis of cellular architecture in a developing tissue
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