The original aim of the MRP N2N, and now BIG N2N, research is, amongst other things, to

  1. build streamlined pipelines to deal with increasingly large numbers of heterogeneous data
  2. integrate these data for further downstream analyses
  3. develop novel tools and approaches for systems biology (inferring and modelling biological networks)
  4. apply these tools and approaches to two main application fields, namely Sustainable Agriculture and Successful Ageing

To this end, we have originally defined five work packages.

In a first work package (WP1), we aim to collect data from the same ‘omics’ type, both generated in house (at UGent) and available in the public domain. Since similar ‘omics’ data, but derived from different platforms and technologies, will be collected, some basic level of curation and statistical normalization will be necessary for further analyses and higher-level integration.

In a second work package (WP2), we will strive for deeper annotation of the data, as well as higher-level integration between different sorts of ‘omics’ data (such as (epi)genomics, transcriptomics, proteomics, and metabolomics data). Multidisciplinary techniques (e.g. machine learning, statistical methods, text-mining) will be applied to obtain better structural and functional annotations and to better understand interactions between different biological molecules.

In WP3, we want to use top-down and bottom-up systems biology approaches to uncover novel emergent properties of specific biological processes and pathways. Although the techniques developed in WP1, WP2 and WP3 will be generic, we will make important contributions to two major areas of research for which Ghent University is already renowned, namely Sustainable Agriculture (WP4) and Successful Ageing (WP5). These research areas are also recognized worldwide as key challenges for a sustainable society.