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仿形(计算机编程)
绘画
计算机科学
计算生物学
生物
数据库
万维网
艺术
视觉艺术
操作系统
作者
Srinivas Niranj Chandrasekaran,Jeanelle Ackerman,Eric Alix,D. Michael Ando,John Arévalo,Melissa Bennion,Nicolas Boisseau,Adriana Borowa,Justin D. Boyd,Laurent Brino,Patrick J. Byrne,Hugo Ceulemans,Carolyn Ch’ng,Beth A. Cimini,Djork-Arné Clevert,Nicole Deflaux,John G. Doench,Thierry Dorval,Régis Doyonnas,Vincenza Dragone
标识
DOI:10.1101/2023.03.23.534023
摘要
Abstract Image-based profiling has emerged as a powerful technology for various steps in basic biological and pharmaceutical discovery, but the community has lacked a large, public reference set of data from chemical and genetic perturbations. Here we present data generated by the Joint Undertaking for Morphological Profiling (JUMP)-Cell Painting Consortium, a collaboration between 10 pharmaceutical companies, six supporting technology companies, and two non-profit partners. When completed, the dataset will contain images and profiles from the Cell Painting assay for over 116,750 unique compounds, over-expression of 12,602 genes, and knockout of 7,975 genes using CRISPR-Cas9, all in human osteosarcoma cells (U2OS). The dataset is estimated to be 115 TB in size and capturing 1.6 billion cells and their single-cell profiles. File quality control and upload is underway and will be completed over the coming months at the Cell Painting Gallery: https://registry.opendata.aws/cellpainting-gallery . A portal to visualize a subset of the data is available at https://phenaid.ardigen.com/jumpcpexplorer/ .
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