Generate, store and share predictive statistical and machine learning models

Provided by:
Research area:
Nano-technology, Chemical Engineering
Dedicated for:
Researchers, Research organisations, Business, Providers
(0.0 /5) 0 reviews

Jaqpot is a user-friendly web-based e-infrastructure containing many data analysis and modelling microservices integrated under a common API. The Jaqpot infrastructure allows for building applications that preprocess data, compute descriptors from raw data (such as electronic images), create, validate, store and share predictive machine learning models and generate reports in standard formats.
Jaqpot user interface allows the end-user to use most Jaqpot functionalities.

OpenRiskNet provides resources to enable users to install their own virtual infrastructures populated with the applications and middleware making up the virtual research environment on public or private cloud resources, as well as in-­house server/workstations. The reference environment (https://home.prod.openrisknet.org/) is provided as a quick entry point to test the OpenRiskNet features. Jaqpot offers the production of predictive models and their sharing within the community as ready-to-use web applications. Case studies have been defined to test and evaluate the solutions provided by OpenRiskNet to the predictive toxicology and risk assessment community especially regarding the usability of the developed APIs and the interoperability layer. These demonstrate the capabilities to satisfy the requirements of the different stakeholder groups including researchers, risk assessors and regulators and present real-world applications like systems biology approaches for grouping compounds, read-across applications using chemical and biological similarity, and identifying areas of concern based on in vitro and in silico approaches for compounds lacking any previous knowledge from animal experiments: 1) Data curation and creation of pre-reasoned datasets and searching, 2) Modelling for Prediction or Read Across, 3) A systems biology approach for grouping compounds, 4) Metabolism Prediction, 5) Identification and Linking of Data related to AOPWiki, 6) Toxicogenomics-based prediction and mechanism identification, 6) Reverse dosimetry and PBPK prediction.

Places and languages
  • World
  • English
Service Availability
Service phase
  • Beta
  • 4.0.3
Last Update
  • 16.10.2020

The EOSC portal is been jointly developed and maintained by the EOSC-hub, eInfraCentral and OpenAIRE-Advance projects funded by the European

Union’s Horizon 2020 research and innovation programme with contribution of the European Commission

2018 EOSC Portal