The amount of biological data and biological data layers is rapidly increasing. Many medical doctors and biomedical researchers without a bio-informatics background are generating large big data so-called ’-omics’ datasets, but do not always have the skills to process, manage or publicly share these data. In this paper, we present MOLGENIS Research, an open-source web-application that allows non-bioinformaticians collect, manage, analyze, visualize and share large and complex biomedical datasets, without the need for advanced bioinformatics skills.

Data flow

MOLGENIS Research contains a selection of apps that are of particular interest to life science investigators. These apps are grouped into the five categories that represent the typical flow of research data: (i) Collect: the gathering or entering of data into the database; (ii) Manage: the inspection and handling of data inside the database; (iii) Analyze: detect patterns and statistically significant differences in the data using algorithms and statistical tests; (iv) Visualize: creating graphs and other visualizations; and (v) Share: making data, the visualizations, and the results available to collaborators or the entire scientific community.

Therefore, the menu structure of MOLGENIS Research is as follows:


  • Single-click importer
  • Step-by-step Importer
  • Manual data entry
  • Remote File Ingest
  • Questionnaire
  • Explore data tables
  • Navigate data folders
  • Edit table metadata
  • Manage users
  • Manage permissions
  • Query and filter data
  • Add and run scripts
  • View execution log
  • Use APIs for R, Python and REST
  • Screen genome with GAVIN
  • Genome Browser
  • Plot data in R how-to
  • Visualization using R
  • Customize reports
  • View data model
  • Setup data catalogue
  • Setup FAIR endpoints
  • Expose data via APIs
  • Tag Wizard
  • Mapping Service
  • Ask a question
  • Change menu
  • Change theme
  • Application log
  • Application settings
  • Reindex database
My account



MOLGENIS Research can be installed first setting up a default MOLGENIS, followed by importing an EMX file with custom menu structure and minimal demo data. In a nutshell:

Demo and citation

This work has been published as Van der Velde et al. MOLGENIS Research: Advanced bioinformatics software for non-bioinformaticians, Bioinformatics. 2019 Mar 15;35(6):1076-1078. doi: 10.1093/bioinformatics/bty742.

Last modified 4 months ago Last modified on 2022-04-05T08:53:40+02:00

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