A guide to the BRAIN Initiative Cell Census Network data ecosystem
Michael Hawrylycz (Allen Institute)
Maryann E. Martone (University of California, San Francisco Veterans Affairs Medical Center)
Giorgio A. Ascoli (George Mason University)
Jan G. Bjaalie (Universitetet i Oslo)
Hong Wei Dong (UCLA School of Medicine)
Satrajit S. Ghosh (Massachusetts Institute of Technology)
Jesse Gillis (University of Toronto)
David R. Haynor (University of Washington)
Boudewijn P. Lelieveldy (Leiden University Medical Center, TU Delft - Pattern Recognition and Bioinformatics)
G.B. More Authors (External organisation)
More Info
expand_more
Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.
Abstract
Characterizing cellular diversity at different levels of biological organization and across AU data: Ple 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.
help_outline