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Dotmotif

A performant, powerful query framework to search for network motifs

Install / Use

/learn @aplbrain/Dotmotif

README

<p align="center"> <img align="center" src="https://user-images.githubusercontent.com/693511/117350563-b58b9900-ae7a-11eb-83ce-9f5f9213145e.png" / width="25%"> <h1 align="center" fontsize="2em">d o t m o t i f</h1> </p> <p align="center">Find graph motifs using intuitive notation</p> <p align="center"> <a href="https://pypi.org/project/dotmotif/"><img alt="PyPI" src="https://img.shields.io/pypi/v/dotmotif?style=for-the-badge"></a> <a href="https://bossdb.org/tools/DotMotif"><img src="https://img.shields.io/badge/Pretty Dope-👌-00ddcc.svg?style=for-the-badge" /></a> <a href="https://bossdb.org/tools/DotMotif"><img src="https://img.shields.io/badge/License-Apache_2.0-blue.svg?style=for-the-badge" /></a> <a href="https://codecov.io/gh/aplbrain/dotmotif"><img alt="Codecov" src="https://img.shields.io/codecov/c/github/aplbrain/dotmotif?style=for-the-badge"></a> </p>

DotMotif is a library that identifies subgraphs or motifs in a large graph. It looks like this:

# Look for all motifs of the form,

# Neuron A synapses on Neuron B:
A -> B
# ...and B inhibits C:
B -> C [type = "inhibitory"]

Examples

| Notebook | Description | |----------|-------------| | <a href="https://colab.research.google.com/gist/j6k4m8/7c5cf55e7feb24685bd13a217cedda1d/dotmotif-search-in-pinky100.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/></a> | Looking for motifs in the IARPA MICrONS Pinky100 Dataset | | <a href="https://colab.research.google.com/gist/j6k4m8/d02259dfedc2321973be4d2e665653f4/dotmotif-search-in-custom-networkx.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/></a> | Motif search in a custom graph | | <a href="https://colab.research.google.com/gist/j6k4m8/919cc1a8162289dd4a6aeb965e800322/dotmotif-search-in-custom-networkx.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/></a> | Subgraph search in the Janelia Hemibrain dataset |

Get Started

If you have DotMotif, a NetworkX graph, and a curious mind, you already have everything you need to start using DotMotif:

from dotmotif import Motif, GrandIsoExecutor

executor = GrandIsoExecutor(graph=my_networkx_graph)

triangle = Motif("""
A -> B
B -> C
C -> A
""")

results = executor.find(triangle)

Parameters

You can also pass optional parameters into the constructor for the dotmotif object. Those arguments are:

| Argument | Type, Default | Behavior | | ----------------------- | --------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | | ignore_direction | bool: False | Whether to disregard direction when generating the database query | | limit | int: None | A limit (if any) to impose on the query results | | enforce_inequality | bool: False | Whether to enforce inequality; in other words, whether two nodes should be permitted to be aliases for the same node. For example, in A->B->C; if A!=C, then set to True | | exclude_automorphisms | bool: False | Whether to return only a single example for each detected automorphism. See more in the documentation |

For more details on how to write a query, see Getting Started.


Citing

If this tool is helpful to your research, please consider citing it with:

# https://doi.org/10.1038/s41598-021-91025-5
@article{Matelsky_Motifs_2021, 
    title={{DotMotif: an open-source tool for connectome subgraph isomorphism search and graph queries}},
    volume={11}, 
    ISSN={2045-2322}, 
    url={http://dx.doi.org/10.1038/s41598-021-91025-5}, 
    DOI={10.1038/s41598-021-91025-5}, 
    number={1}, 
    journal={Scientific Reports}, 
    publisher={Springer Science and Business Media LLC}, 
    author={Matelsky, Jordan K. and Reilly, Elizabeth P. and Johnson, Erik C. and Stiso, Jennifer and Bassett, Danielle S. and Wester, Brock A. and Gray-Roncal, William},
    year={2021}, 
    month={Jun}
}

Related Skills

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GitHub Stars90
CategoryData
Updated26d ago
Forks10

Languages

Python

Security Score

100/100

Audited on Mar 2, 2026

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