Demonstration on OpenRiskNet approach on modelling for prediction or read across (ModelRX case study)

Webinar (organized by OpenRiskNet)
11 Jun 2019

Activity details

Tuesday, 11 June 2019, 16:00 CEST

Presenters: Philip Doganis and Haralambos Sarimveis (National Technical University of Athens, Greece)

The ModelRX case study contributes to OpenRiskNet by providing:

  • computational methods to support  suitability assessment of existing data and identification of analogues;
  • predictive modelling functionalities, which are essential in the field of final risk assessment.

During the webinar, we will focus on the Jaqpot platform within the ModelRX case study. Starting from a dataset in Jaqpot v4 at http://www.jaqpot.org, we will apply an algorithm to create a model and get predictions, which are accompanied by QPRF (QSAR prediction reporting format) report.

We will also introduce the new Jaqpot v5 GUI (Graphical User Interface) at https://app.jaqpot.org that allows users easy upload of models they have developed in their own Python or R environment, make them available as web services and offers powerful sharing functionalities of online resources.

Registration: https://attendee.gotowebinar.com/register/2389609700743262987 

Organisations involved

Johannes Gutenberg-Universität Mainz (JGU)
National Technical University of Athens (NTUA)

Resources & Training materials

Webinar recording
Demonstration on OpenRiskNet approach on modelling for prediction or read across (ModelRX case study)
Philip Doganis and Haralambos Sarimveis (National Technical University of Athens, Greece)
25 Jun 2019

Target audience: Risk assessors, Researchers, Data modellers, Bioinformaticians
Open access: yes
Licence: Attribution-ShareAlike 4.0 International (CC BY-SA 4.0)
Organisations involved: NTUA
Webinar recording
Presentation
Demonstration on OpenRiskNet approach on modelling for prediction or read across (ModelRX case study)
Philip Doganis and Haralambos Sarimveis (National Technical University of Athens, Greece)
24 Jun 2019
Additional materials:
Slides

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

Links and additional materials