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biologycell biologycell imagingHomo sapiensimage processinglife sciencesmachine learningmicroscopy
This bucket contains multiple datasets (as Quilt packages) created by the Allen Institute for Cell Science. The types of data included in this bucket are listed below:
bioinformaticsbiologycancercell biologycell imagingcell paintingchemical biologycomputer visioncsvdeep learningfluorescence imaginggenetichigh-throughput imagingimage processingimage-based profilingimaginglife sciencesmachine learningmedicinemicroscopyorganelle
The Cell Painting Gallery is a collection of image datasets created using the Cell Painting assay. The images of cells are captured by microscopy imaging, and reveal the response of various labeled cell components to whatever treatments are tested, which can include genetic perturbations, chemicals or drugs, or different cell types. The datasets can be used for diverse applications in basic biology and pharmaceutical research, such as identifying disease-associated phenotypes, understanding disease mechanisms, and predicting a drug’s activity, toxicity, or mechanism of action (Chandrasekaran et al 2020). This collection is maintained by the Carpenter–Singh lab and the Cimini lab at the Broad Institute. A human-friendly listing of datasets, instructions for accessing them, and other documentation is at the corresponding GitHub page abou...
biologyfluorescence imagingimage processingimaginglife sciencesmicroscopyneurobiologyneuroimagingneuroscience
This data set, made available by Janelia's FlyLight project, consists of fluorescence images of Drosophila melanogaster driver lines, aligned to standard templates, and stored in formats suitable for rapid searching in the cloud. Additional data will be added as it is published.
biologycell imagingfluorescence imaginghigh-throughput imagingimaginglife sciencesmachine learningmicroscopy
Quantifying cell morphology using images and machine learning models has proven to be a powerful tool to study the response of cells to treatments. However, the models used to quantify cellular morphology are typically trained with a single microscopy imaging type and under controlled experimental conditions. This results in specialized models that cannot be reused across biological studies because the technical specifications do not match (e.g., different number of channels), or because the target experimental conditions are out of distribution. We have created CHAMMI-75, a large-scale dat...
biologycell biologycomputer visionelectron microscopyimaginglife sciencesmicroscopysegmentation
The Automated Segmentation of intracellular substructures in Electron Microscopy (ASEM) project provides deep learning models trained to segment structures in 3D images of cells acquired by Focused Ion Beam Scanning Electron Microscopy (FIB-SEM). Each model is trained to detect a single type of structure (mitochondria, endoplasmic reticulum, golgi apparatus, nuclear pores, clathrin-coated pits) in cells prepared via chemically-fixation (CF) or high-pressure freezing and freeze substitution (HPFS). You can use our open source pipeline to load a model and predict a class of sub-cellular structur...
bioinformaticselectrophysiologylife sciencesmicroscopyneurophysiologyneuroscience
The SPARC Datasets comprise a collection of scientific data that is focused on bridging the body and the brain. The datasets focus on neural connectivity, organ innervation and detailed anatomical mapping of the peripheral nervous system. SPARC datasets distinguish themselves from other data resources through its multi-modal approach to scientific data and integrates molecular, imaging, timeseries and other datatypes associated with the interaction between the peripheral nervous system and organs. SPARC data provides a unique integrated effort to develop next generation mapping of anatomical ...
biologycancerclassificationcomputational pathologydicomgrand-challenge.orghealthHomo sapiensimaginglife sciencesmachine learningmedical image computingmedical imagingmedicinemicroscopysegmentation
A public-access archive of skin lesion images, supporting teaching, research, and the development and evaluation of diagnostic algorithms.
biologyfluorescence imagingimage processingimaginglife sciencesmicroscopyneurobiologyneuroimagingneuroscience
This data set, made available by Janelia's MouseLight project, consists of images and neuron annotations of the Mus musculus brain, stored in formats suitable for viewing and annotation using the HortaCloud cloud-based annotation system.
biologycell biologycell imagingcomputer visionfluorescence imagingimaginglife sciencesmachine learningmicroscopy
The OpenCell project is a proteome-scale effort to measure the localization and interactions of human proteins using high-throughput genome engineering to endogenously tag thousands of proteins in the human proteome. This dataset consists of the raw confocal fluorescence microscopy images for all tagged cell lines in the OpenCell library. These images can be interpreted both individually, to determine the localization of particular proteins of interest, and in aggregate, by training machine learning models to classify or quantify subcellular localization patterns.
analysis ready databrain imagesbrain modelsimaginginfrastructurejsonlife sciencesmachine learningmetadatamicroscopyneuroimagingneuroscienceniftizarr
The BRAIN Initiative Connectivity Across Scales (CONNECTS) program is working to create detailed maps of brain wiring across different species and scales, using advanced imaging technologies. APEX supports this effort by serving as a central hub that brings together and coordinates data and tools from research focused on brain connectivity in humans and animals. Together, these efforts aim to improve our understanding of how the brain is structured and functions.
biodiversitybioinformaticsbiologybiomolecular modelingbrain imagescell biologycell imagingcziimaginglife sciencesmachine learningmicroscopymodelproteinzarr
This dataset contains a diverse range of imaging biological data and models. The data is sourced and curated by a team of experts at CZI and is made available as part of these datasets only when it is not publicly accessible or requires transformations to support model training.
cancerdigital pathologyfluorescence imagingimage processingimaginglife sciencesmachine learningmedical imagingmicroscopyradiology
Imaging Data Commons (IDC) is a repository within the Cancer Research Data Commons (CRDC) that manages imaging data and enables its integration with the other components of CRDC. IDC hosts a growing number of imaging collections that are contributed by either funded US National Cancer Institute (NCI) data collection activities, or by the individual researchers.Image data hosted by IDC is stored in DICOM format.
fluorescence imagingGeneLabgeneticgenetic mapslife sciencesmicroscopyNASA SMD AI
Fluorescence microscopy images of individual nuclei from mouse fibroblast cells, irradiated with Fe particles or X-rays with fluorescent foci indicating 53BP1 positivity, a marker of DNA damage. These are maximum intensity projections of 9-layer microscopy Z-stacks.
brain imagesimaginglife sciencesmicroscopyneurobiologyneuroimagingneuroscienceniftinon-human primate
Brain/MINDS Marmoset Connectivity Resource (BMCR) is a resource that provides access to anterograde and retrograde neuronal tracer data, made available by Brain/MINDS project. It is currently restricted to injections into the prefrontal cortex of a marmoset brain but is planned to include injections into entire cortical areas and representative subcortical brain regions.
biologydigital preservationHomo sapiensimage processingimaginglife scienceslight-sheet microscopymagnetic resonance imagingmedical imagingmicroscopyMus musculusneurobiologyneuroimagingneuroscienceRattus norvegicusvolumetric imagingzarr
BrainGlobe provides an archive and standardised interface to anatomical atlases from multiple species. This dataset includes these atlases, and other data (e.g. sample neuroanatomy data) to allow the greatest use of the atlases.
biologycell imagingcell paintingfluorescence imaginghigh-throughput imagingimaginglife sciencesmicroscopy
The Cell Painting Image Collection is a collection of freely downloadable microscopy image sets. Cell Painting is an unbiased high throughput imaging assay used to analyze perturbations in cell models. In addition to the images themselves, each set includes a description of the biological application and some type of "ground truth" (expected results). Researchers are encouraged to use these image sets as reference points when developing, testing, and publishing new image analysis algorithms for the life sciences. We hope that the this data set will lead to a better understanding of w...
bioinformaticsbiologybrain imagescell imagingcomputer visionfluorescence imaginghigh-throughput imagingimage processingimagingion channelslife sciencesmachine learningmicroscopymorphological reconstructionsMus musculusneurobiologyneuroimagingneuroscienceproteinsegmentationzarr
This dataset was generated using E11.bio's PRISM technology (Protein Reconstruction and Identification through Multiplexing), a platform that combines viral barcoding, expansion microscopy, and iterative immunolabeling for large-scale neuronal reconstruction.Neurons in the mouse hippocampal CA3 were transduced with a library of adeno-associated viruses (AAVs) encoding diverse “protein bits”—small epitope tags that act as combinatorial barcodes. Tissue was then processed with an expansion microscopy protocol, physically enlarging the sample ~5× to achieve an effective voxel size of ~35 × 3...
biologycell biologycell imagingepigenomicsgene expressionhistopathologyHomo sapiensimaginglife sciencesmedicinemicroscopyneurobiologyneurosciencesingle-cell transcriptomicstranscriptomics
The Seattle Alzheimer's Disease Brain Cell Atlas (SEA-AD) consortium strives to gain a deep molecular and cellular understanding of the early pathogenesis of Alzheimer's disease and is funded by the National Institutes on Aging (NIA U19AG060909). The SEA-AD datasets available here comprise single cell profiling (transcriptomics and epigenomics) and quantitative neuropathology. To explore gene expression and chromatin accessibility information, the single-cell profiling data includes: snRNAseq and snATAC-seq data from the SEA-AD donor cohort (aged brains which span the spectrum of Alzhe...
biodiversitybioinformaticsbiologybiomolecular modelingbrain imagescell biologycell imagingcziimaginglife sciencesmachine learningmicroscopymodelproteinzarr
This dataset contains a diverse range of imaging biological data and models. The data is sourced and curated by a team of experts at CZI and is made available as part of these datasets only when it is not publicly accessible or requires transformations to support model training.
brain imagescomputer visionlife sciencesmicroscopyneurobiologysegmentation
We introduce DHARANI, the first online platform with three-dimensional (3D) histological reconstructions of the developing human brain from 14 to 24 gestational weeks (GW) across the five fetal brains. DHARANI features 5132 Nissl, hematoxylin and eosin stained, 20 µm coronal and sagittal sections, postmortem MRI, and a neuroanatomical atlas with 466 annotated sections covering ∼500 brain structures. It is accessible online at https://brainportal.humanbrain.in/publicview/index.html. The 3D reconstruction enables a volumetric view of the fetal brain, allowing visualization in all three planes ak...