A guide to the BRAIN Initiative Cell Census Network data ecosystem
PLOS Biology·202351 cites
20232026
51
Hawrylycz, Michael and Martone, Maryann E. and Ascoli, Giorgio A. and Bjaalie, Jan G. and Dong, Hong-Wei and Ghosh, Satrajit S. and Gillis, Jesse and Hertzano, Ronna and Haynor, David R. and Hof, Patrick R. and Kim, Yongsoo and Lein, Ed and Liu, Yufeng and Miller, Jeremy A. and Mitra, Partha P. and Mukamel, Eran and Ng, Lydia and Osumi-Sutherland, David and Peng, Hanchuan and Ray, Patrick L. and Sanchez, Raymond and Regev, Aviv and Ropelewski, Alex and Scheuermann, Richard H. and Tan, Shawn Zheng Kai and Thompson, Carol L. and Tickle, Timothy and Tilgner, Hagen and Varghese, Merina and Wester, Brock and White, Owen and Zeng, Hongkui and Aevermann, Brian and Allemang, David and Ament, Seth and Athey, Thomas L. and Baker, Cody and Baker, Katherine S. and Baker, Pamela M. and Bandrowski, Anita and Banerjee, Samik and Bishwakarma, Prajal and Carr, Ambrose and Chen, Min and Choudhury, Roni and Cool, Jonah and Creasy, Heather and D'Orazi, Florence and Degatano, Kylee and Dichter, Benjamin and Ding, Song-Lin and Dolbeare, Tim and Ecker, Joseph R. and Fang, Rongxin and Fillion-Robin, Jean-Christophe and Fliss, Timothy P. and Gee, James and Gillespie, Tom and Gouwens, Nathan and Zhang, Guo-Qiang and Halchenko, Yaroslav O. and Harris, Nomi L. and Herb, Brian R. and Hintiryan, Houri and Hood, Gregory and Horvath, Sam and Huo, Bingxing and Jarecka, Dorota and Jiang, Shengdian and Khajouei, Farzaneh and Kiernan, Elizabeth A. and Kir, Huseyin and Kruse, Lauren and Lee, Changkyu and Lelieveldt, Boudewijn and Li, Yang and Liu, Hanqing and Liu, Lijuan and Markuhar, Anup and Mathews, James and Mathews, Kaylee L. and Mezias, Chris and Miller, Michael I. and Mollenkopf, Tyler and Mufti, Shoaib and Mungall, Christopher J. and Orvis, Joshua and Puchades, Maja A. and Qu, Lei and Receveur, Joseph P. and Ren, Bing and Sjoquist, Nathan and Staats, Brian and Tward, Daniel and van Velthoven, Cindy T. J. and Wang, Quanxin and Xie, Fangming and Xu, Hua and Yao, Zizhen and Yun, Zhixi and Zhang, Yun Renee and Zheng, W. Jim and Zingg, Brian
Characterizing cellular diversity at different levels of biological organization and across data modalities is a prerequisite to understanding the function of cell types in the brain. Classification of neurons is also essential to manipulate cell types in controlled ways and to understand their variation and vulnerability in brain disorders. The BRAIN Initiative Cell Census Network (BICCN) is an integrated network of data-generating centers, data archives, and data standards developers, with the goal of systematic multimodal brain cell type profiling and characterization. Emphasis of the BICCN is on the whole mouse brain with demonstration of prototype feasibility for human and nonhuman primate (NHP) brains. Here, we provide a guide to the cellular and spatial approaches employed by the BICCN, and to accessing and using these data and extensive resources, including the BRAIN Cell Data Center (BCDC), which serves to manage and integrate data across the ecosystem. We illustrate the power of the BICCN data ecosystem through vignettes highlighting several BICCN analysis and visualization tools. Finally, we present emerging standards that have been developed or adopted toward Findable, Accessible, Interoperable, and Reusable (FAIR) neuroscience. The combined BICCN ecosystem provides a comprehensive resource for the exploration and analysis of cell types in the brain.
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