# Model organism neural circuit knowledge graph

> **NIH NIH U24** · CALIFORNIA INSTITUTE OF TECHNOLOGY · 2021 · $259,479

## Abstract

Project Summary
To extract greater value from extensive but disparate and siloed data relevant to neural circuits, we will leverage
the ontologies, bioinformatics, and curation of the Alliance of Genome Resources to derive an artificial
intelligence (AI) ready knowledge graph. Participation of a computational neuroscientist who uses AI for neural
circuit analyses will help specify the form of the knowledge graph, demonstrate the utility of the graphs, extend
the graphs from a focus on the well-defined nervous system of Caenorhabditis elegans to the similarly well-
defined mouse retina, and connect with neuroscience researchers who are starting to applying AI to neural
circuits. Known entities (such as neurons, small molecules, and neuropeptides) and Ontologies (anatomy,
relations, and experimental evidence) provide the underlying data of the graph. Curated assertions provide the
knowledge, e.g., synaptic or functional connections between neurons, neuropeptide has a specific receptor, or
a neuropeptide is expressed in a specific neuron). In this graph model, entities are the nodes, ontological
relationships are the edges. These provide an inferred knowledge graph supported by evidence backed
assertions. This type of knowledge graph can be applied to biological pathways that are based on phenotype
observations including expression, neuronal activity and organismal behavior rather than physical interactions
or enzymatic activities such as those used to describe biochemical pathways. To accomplish generation of
knowledge graphs, we will refine the relevant vocabularies to focus on relations used in neural circuit research,
we will adjust existing infrastructure to handle the appropriate ontologies, data models, and curation tools for
neural circuit data, and we will incentivize expert contributions by arranging short reviews coupled to computable
assertions. The knowledge graph will be used by local AI experts, published on the internet, and tested by a
hackathon.

## Key facts

- **NIH application ID:** 10412857
- **Project number:** 3U24HG010859-03S2
- **Recipient organization:** CALIFORNIA INSTITUTE OF TECHNOLOGY
- **Principal Investigator:** CAROL J BULT
- **Activity code:** U24 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $259,479
- **Award type:** 3
- **Project period:** 2019-09-18 → 2024-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10412857

## Citation

> US National Institutes of Health, RePORTER application 10412857, Model organism neural circuit knowledge graph (3U24HG010859-03S2). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10412857. Licensed CC0.

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