Jaqpot is a computational platform for in silico modelling of chemical compounds, that provides both access to its services both over a User Interface (GUI) and an Application Programming Interface (API). It is a cloud-ready application that uses the benefits of Java, R and Python, having incorporated functionality by various established and open-source machine learning and data analysis toolkits, while algorithms in any programming algorithm can be added to Jaqpot. A new version of the UI and API is in preparation and will be released within 2019.
The UI is a user-friendly path for non-developers to explore its functionality, while the API provides developers with great power to enhance existing 3rd-party apps, tools, Graphical User Interfaces (GUIs), and Jupyter notebooks by integrating integrate Jaqpot modelling and analysis services into them.
At the same time, third parties can easily contribute and integrate their services into the Jaqpot infrastructure provided that they make them API compliant. Thus, Jaqpot’s architecture paves the way to the creation of a modeling ecosystem where independent systems contribute and collaborate while maintaining their autonomy, provided that they adhere to the API.
Jaqpot was originally developed by NTUA during the FP7 OpenTox project according to the OpenTox APIs and considerably extended in the H2020 eNanoMapper project to include additional modelling functionalities, some of them addressing the special requirements emerging from the complex and multi-perspective characterisation of NMs. The Jaqpot API has been integrated in the ongoing H2020 OpenRiskNet project as a component of the overall e-infrastructure, with extensions to address additional modelling and analysis requirements and use cases, such as biokinetics and dose-response modelling. The OpenRiskNet infrastructure will live on through the NanoCommons project.
- Provided by: National Technical University of Athens
- Type: In silico modelling
- Applicability domain: Provides modelling functionality for any NanoCommons-related area (such as Engineered Nanomaterials, Environmental Safety, Nanomedicine) when provided with a relevant dataset
- Topic: Predictive modelling
- Contact: Haralambos Sarimveis
- For researchers
- For industry
- For regulators