Jupyter Notebooks

Interactive computing and workflows sharing
A collection of Jupyter notebooks developed for and with the OpenRiskNet VRE. Project Jupyter is a non-profit, open-source project, born out of the IPython Project in 2014 as it evolved to support interactive data science and scientific computing across all programming languages. Jupyter is developed in the open on GitHub, through the consensus of the Jupyter community (Read more at http://jupyter.org/)

For developers
For end-users
Workflow, Visualisation tool, Helper tool, Software, Analysis tool, Processing tool
Visualisation and reporting, Processing and analysis
Applicability domain:
Computational modelling, Toxicology, Bioinformatics
Targeted users:
Software Developers, Risk assessors, Researchers, Students
Relevant OpenRiskNet case studies:
  • AOPLink - Identification and Linking of Data related to AOPWiki
  • DataCure - Data curation and creation of pre-reasoned datasets and searching
  • MetaP - Metabolism Prediction
  • ModelRX - Modelling for Prediction or Read Across
  • RevK - Reverse dosimetry and PBPK prediction
  • SysGroup - A systems biology approach for grouping compounds
  • TGX - Toxicogenomics-based prediction and mechanism identification

Provided by:
Project Jupyter
Login required:
Implementation status:
Containerised, Graphical user interface available, Available as web service
Integration status:
Integrated application
Service integration operations completed:
Utilises the OpenRiskNet APIs to ensure that each service is accessible to our proposed interoperability layer.
Is annotated according to the semantic interoperability layer concept using defined ontologies.
Is containerised for easy deployment in virtual environments of OpenRiskNet instances.
Has documented scientific and technical background.
Is deployed into the OpenRiskNet reference environment.
Is listed in the OpenRiskNet discovery services.
Is listed in other central repositories like eInfraCentral, bio.tools and TeSS (ELIXIR).
Provides legal and ethical statements on how the service can be used.

Resources & Training

Workflow: Access TG-GATEs data for seleted compounds, select differentially expressed genes and identifier relevant pathways
Thomas Exner
13 Sep 2018
Example workflow based on OpenRiskNet tools - Pathway identification workflow related to DataCure and AOPlink case studies. This notebook downloads TG-Gates data of 4 compounds and selects genes overexpressed in all sample. The Affymetrix probe sets are then translated into Ensembl gene identifiers using the BridgeDB service and pathways associated with the genes are identified using the WikiPathways service.

Publisher: OpenRiskNet
Target audience: Risk assessors, Researchers, Data modellers
Open access: yes
Licence: Attribution-ShareAlike 4.0 International (CC BY-SA 4.0)
Organisations involved: EwC