BrainKB
Facilitating Evidence-Based Decision Making to Unlock the Mysteries of the Mind
Key Features
Powerful tools for neuroscience knowledge extraction and management
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Ingest Knowledge Graphs
Easily upload neuroscience KGs in JSON-LD or TTL
Upload Knowledge Graph files in JSON-LD or Turtle format. Seamlessly integrate your neuroscience data into the BrainKB ecosystem.
What is BrainKB?
BrainKB is a platform designed to support neuroscience research by structuring and organizing scientific knowledge using knowledge graphs (KGs) for delivering evidence-based insights.
Structured Knowledge
BrainKB structures neuroscience knowledge into an accessible and scalable knowledge graph.
Data Exploration
It provides tools for searching, exploring, visualizing, and analyzing neuroscience data.
Community Contribution
Researchers can contribute new findings, represented as assertions with supporting evidence from publications.
Collaboration Hub
BrainKB aims to be the go-to resource for neuroscientists worldwide, fostering collaboration and accelerating discoveries.
Use Cases
BrainKB is actively developing use cases to support neuroscience research and knowledge management
Each use case includes ingestion, public view, and feedback components integrated with our Knowledge Graph
HMBA Taxonomy
Case 1
Hierarchical taxonomy management for neuroscience data classification and organization.
Resources Extraction
Case 2
Extract and structure resources from unstructured documents and publications.
Resource Metadata Expansion
Case 3
Expand and enrich resource metadata including datasets with comprehensive information.
Neuroscientific Entity Extraction
Case 4
Extract and identify neuroscience entities from text using agentic AI.
Assertion Evidence
Case 5
Link scientific assertions with supporting evidence from publications and research.
Brain Visualization
Future Consideration
Connect all information through interactive brain visualization for comprehensive knowledge exploration.
About Use Cases
Each use case in BrainKB includes three key components that work together to create a comprehensive knowledge management system:
- •Ingestion Process: Data submission mechanisms (public or maintainer-only, depending on the use case)
- •Public View & Interactions: Accessible interfaces for exploring and interacting with the knowledge
- •Public Feedback: Community input and validation mechanisms
Development Status
Use cases are marked with different statuses to indicate their current state:
All use cases are integrated with (or are on a process of integration) the BrainKB Knowledge Graph, enabling seamless data flow and comprehensive knowledge representation.
View Full Planning DiscussionKnowledge Graph Metrics
Number of unique samples from different models.
As of November 2025
Structured Models
Structured models used in BrainKB.
Genome Annotation Schema
A data model designed to represent types and relationships of an organism's annotated genome.
Read more→Anatomical Structure Schema
A data model designed to represent types and relationships of anatomical brain structures.
Read more→Library Generation Schema
A schema designed to represent types and relationships of samples and digital data assets generated during multimodal genomic data processes.
Read more→Evidence Assertion Ontology
A data model designed to represent types and relationships of evidence and assertions.
Read more→Powered by Advanced AI Agents
BrainKB leverages cutting-edge agentic frameworks for structured information extraction. Our platform utilizes STRUCTSENSE, a task-agnostic agentic framework that enables sophisticated structured information extraction.
Research Citation:
Chhetri, T.R., Chen, Y., Trivedi, P., Jarecka, D., Haobsh, S., Ray, P., Ng, L. and Ghosh, S.S., 2025. STRUCTSENSE: A Task-Agnostic Agentic Framework for Structured Information Extraction with Human-In-The-Loop Evaluation and Benchmarking. arXiv preprint arXiv:2507.03674.
See Research Paper