Project Summary
BRAIN Initiative Cell Census Network (BICCN) is completing a comprehensive cell census of the adult mouse
brain, and BRAIN Initiative Cell Atlas Network (BICAN) will extend this work with emphasis on human and non-
human primates. Effectively organizing, summarizing, accessing, and refining these atlases is critical to
maximizing their impact on science. This proposal is to develop an extensible Brain Cell Knowledge Base
(BCKB) to ingest and standardize comprehensive cell type information from BICAN’s development of a
multimodal, multi-species brain cell atlas and disseminate that atlas as an open and interactive community
resource for advancing knowledge of the brain. The BCKB will be initialized during this project with multi-
dimensional brain cell type classifications from BICCN and will expand as data and knowledge are produced by
BICAN researchers.
Under Aim 1, we will create an adaptive knowledge graph for linking brain cell information. Spatial aggregation
will be done using common coordinate frameworks. A flexible graph-based data model will capture discrete and
continuous cell type relationships. The work will start with cross-species MOp data and comprehensive whole-
brain mouse datasets from BICCN and later extend into BICAN’s whole-brain molecular and spatial
transcriptomics data in human and non-human primates as such data becomes available. Anchoring of
taxonomies in single cell molecular and spatial transcriptomics provides a robust framework for integrating
multimodal data that is spatially mapped and/or cell types mapped. An ecosystem of tools for curating,
annotating, mapping, and visualization of cell type data will be created in Aim 2. We will build and extend tools,
such as the initial Cell Types Cards showcasing BICCN’s MOp results, so BICAN teams and public labs can
share and refine brain cell type taxonomies and anatomical integration. The tools framework developed for this
aim will provide a central hub, akin to an “app store,” to access our tools and others from the community to
interact with cell type data. This connected tools framework will streamline scientific workflows and encourage
FAIR practices. As part of Aim 3, we will develop an infrastructure to link brain cell data and knowledge. This
infrastructure will enable ingesting, storing, searching, and curating neuroscientific information from multiple
sources into a linked information platform. This knowledge infrastructure will help connect disparate pieces of
cell type information using expert annotations, machine-learning inferences, and derivations using provenance
mechanisms. We will use Allen Institute’s Brain Knowledge Platform for initial implementation. Finally, in Aim 4
we will gather, curate, and integrate information and knowledge from BICAN teams by conducting annual hands-
on training and feedback workshops. These events will create engagement within and outside BICAN projects
and foster community-based evolution, sustainability, and governance.
