{"url":"/dataset/nih-3t3-microtubule-cell-dataset","name":"NIH 3T3 microtubule cell dataset","full_name":null,"description_markdown":"The data consists of 21 images of microtubules in PFA-fixed NIH 3T3 mouse embryonic fibroblasts (DSMZ: ACC59) labeled with a mouse anti-alpha-tubulin monoclonal IgG1 antibody (Thermofisher A11126, primary antibody) and visualized by a blue-fluorescent Alexa Fluor 405 goat anti-mouse IgG antibody (Thermofisher A-31553, secondary antibody). Acquisition of the images was performed using a confocal microscope (Olympus IX81).\r\n\r\nThe images feature cell clusters of various sizes at various scales and densities, with no underlying cluster assignment.\r\n\r\nThe images belong to Ulrike Rölleke and Sarah Köster (University of Göttingen).","description_withheld":null,"homepage":"https://github.com/leosuchan/Xist","introduced_date":"2023-01-30","introduced_date_note":null,"introduced_by":{"paper":"/paper/a-scalable-clustering-algorithm-to","title":"A scalable clustering algorithm to approximate graph cuts","first_author":null,"url":null},"license":null,"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[{"name":"2D Object Detection","url":"/task/2d-object-detection","datasets_with_task":"/datasets/task/2d-object-detection"},{"name":"Image Clustering","url":"/task/image-clustering","datasets_with_task":"/datasets/task/image-clustering"}],"languages":[],"variants":["NIH 3T3 microtubule cell dataset"],"data_loaders":[],"num_papers_in_archive":1,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-25T09:33:49+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}