• Infrastructure

    Data analysis, integration
    and stewardship

Data analysis, integration and stewardship

Past and Present

In recent years, we have seen an explosion of -omics data. Many analysis pipelines for genomics, transcriptomics, proteomics and metabolomics are available, but to make integrated use of those data, and to translate those data into actionable knowledge (e.g. new bioengineering strategies, new diagnostic routines, new drug targets) is a major bottleneck. This is particularly true for researchers who do not have access to state-of-the-art bioinformatics expertise, tools or analysis environments. The X-omics infrastructure is there to enable efficient data integration, and does this for data generated within X-omics and external datasets. X-omics adopts the widely recognized FAIR principles, and takes them a step further: the X-omics infrastructure helps researchers to make data FAIR at the source, to facilitate reuse of their data, and to make their data analysis workflows transparent and reproducible.

Challenges to be addressed by the infrastructure

To facilitate analysis, integration and stewardship of X-omics data by developing: 

  1. an integrated strategy for experimental design that will enable the analysis of complex samples with multiple omics technologies.
  2. a data infrastructure based on FAIR principles and design methods to combine different data sources from analytical omics-platforms and other related data to obtain a comprehensive view of complex systems.
  3. an expert community and making the capabilities of the Netherlands X-omics Initiative available for external users.


  • Peter-Bram 't Hoen

    Prof.dr. Peter-Bram ’t Hoen is full professor in bioinformatics at RadboudUMC (Centre for Molecular and Biomolecular Informatics). Before that, he was postdoc, assistant and associate professor in the Human Genetics department at Leiden University Medical Center. His group studied the aetiology of rare muscular dystrophies using state-of-the-art molecular technologies. He was among the first researchers in the Netherlands to implement microarray and (novel) RNA-sequencing technologies, and organized many (inter)national courses on these topics. With these new technologies, he identified major players and mechanisms in the transcriptional and post-transcriptional regulation of gene expression in health and disease. His main drive is to optimally analyze and interpret large -omics data sets. In their interpretation, he typically goes beyond standard (pathway) analysis methods and develops and employs automated knowledge discovery approaches and new statistical routines. This resulted in the prediction and validation of novel biomarkers, novel protein: protein interactions, and new candidate drugs. Apart from his leading role in the X-omics Data Analysis, Integration and Stewardship pillar, ‘t Hoen is member of the International Rare Diseases Research Consortium (IRDiRC ) taskforce on data mining and drug repurposing, board member of the research working group European Reference Network on neuromuscular diseases (EURO-NMD) and management team member of the personal health train consortium, developing a data infrastructure to advance healthcare and biomedical science through interoperable and federated data management.  

  • Morris Swertz

    Prof.dr. Morris Swetz is associate professor Big Data in Biomedical Science and Head of Genomics Coordination Center at University Medical Center Groningen. He develops innovative and powerful methods for efficient modelling, production and evolution of flexible biological software infrastructures for post-genomic research. These methods allow researchers to manage, analyze and integrate large datasets at multiple molecular levels to answer various research questions. These methods and tools are now evolving into ‘eLaboratories’ and ‘eScience’: integrated systems of tools that speed up biomedical research by integrating large-scale genotyping and phenotyping experiments such as microarrays, proteomics, metabolomics, SNP genotyping, and deep sequencing. He developed MOLGENIS as an open source framework to handle the enormous flow of post-genomic data. His work is disseminated through local (Groningen Bioinformatics Center, LifeLines), national (Netherlands Bioinformatics Center/BioAssist program) and international (BBMRI, ELIXIR, SolveRD) consortia. 

Other PI's involved:

  Peter-Bram ’t Hoen (Radboudumc)
  Morris Swertz (UMCG)
  Ariaan Siezen (Radboudumc)
  Ies Nijman (UU)
  Jeroen de Ridder (UMCU)
  Peter Horvatovitch (RUG)
  Victor Guryev (UMCG)
  Lude Franke (UMCG)
  Rainer Bischoff (RUG)
  Katy Wolstencroft (UL)
  Marcel Reinders (LUMC/TUD)
  Irene Nooren (SurfSARA)
  Amy Harms (UL)
  Leon Mei (LUMC)

This research was (partially) funded by NWO, project 184.034.019