We integrate cutting-edge Machine Learning and Artificial Intelligence algorithms with graph-structured data to empower scientists and researchers of all disciplines with state of the art tools to gain greater insights from their data.
GAMMA enables academics, students, data scientists, and professionals of all kinds to choose from a pool of specialist, native graph ML algorithms, and effortlessly run these advanced tools on their own datasets.
With intuitive tools for importing your data, performing analysis and exporting results, GAMMA enables simple yet scalable ML, whether you need a simple label propagation algorithm or an advanced Deep Learning model.
FAST, INSIGHTFUL ANALYSIS
The GAMMA App integrates directly into the neo4j Desktop platform and brings together a variety of technologies designed for use on both small and massive datasets. As data scientists and machine learning researchers, we appreciate the value of rapid prototyping and easy integration. It is for this reason we have developed a python plugin system for neo4j which brings the power of python's rich eco-system of analytics and ML libraries to your graphs (numpy, tensorflow, keras, sci-kit learn, pandas, networkx, and so many more...)
GAMMA provides a range of ML algorithms for tasks including classification, prediction, clustering, and anomaly detection that can be used in a vast range of applications. Here's just a few examples:
Predicting structural information for amino acids, proteins, and enzymes
Network analysis and cyber security
Training data enrichment
Identification of role, dependence, and influence in social networks
Enriching isolated models with appropriate background from knowledge graphs
Predicting chemical properties such as the effectiveness of a drug against a given condition