Uses Sharphound, Bloodhound and Neo4j to produce an actionable list of attack paths for targeted remediation.
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Updated
Jul 9, 2024 - Python
Uses Sharphound, Bloodhound and Neo4j to produce an actionable list of attack paths for targeted remediation.
Develop a personalized recommendation system using a Knowledge Graph to model relationships between users, products, and interactions. Utilizing Python, Neo4j, Cypher, and Py2neo, this project aims to enhance user satisfaction through efficient data management and advanced recommendation algorithms.
An exploratory, tutorial and analytical view of the Unified Medical Language System (UMLS) & the software/technologies provided via being a free UMLS license holder. This repo will subset 2021AB UMLS native release, introduce/build upon UMLS provided tools to load a configured subset into first a relational database --> MySQL, SQLite, PostgreSQL…
Python uploader of GTFS data to Neo4j db. Creates correct graph according to the GTFS static specification (https://developers.google.com/transit/gtfs).
Here we will sort out a variety of interesting Python library learning
Analyze contributors to PyPi using Libraries.io data
A tool to import SnpEff annotated files to a Neo4j Graph database
A tool to aggregate and load TB data to Neo4j
Programmed RESTful API endpoints using py2neo to execute raw cypher queries and OGM on Neo4j database to query Game of Thrones graph.
Cypher access to Neo4J via IPython
Working through "The Movie Graph" as Py2Neo
COMBAT-TB model is a Chado inspired graph model for genome annotation.
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