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Resolve Chronic Inflammation and Achieve Healthy Ageing by Understanding Non-regenerative Repair

Statistical evaluation and mathematical modelling

RESOLVE’s central data-platform allows for highly efficient data management and analysis.

Data management RESOLVE is currently developing a LIMS (Laboratory Information Management System) that mirrors the workflows and the functional interrelationsship of RESOLVE’s research approaches.

The LIMS is web-based to provide an easy interaction with the different partners in the project.

Data mining

RESOLVE focuses on incorporating the knowledge of advanced data mining techniques into the analysis of complex data. This analysis concentrates in literature text mining, DNA Arrays mining and proteomics data mining. The three specific new forms of data mining are:

  • Association Rules Discovery
  • Factorization by (non-smooth) Non-Negative Matrix Factorization (ns-NNMF)
  • Literature Mining, coupled with more traditional ones such as clustering or biological enrichment (including the novel co-occurrence analysis).


Prior to the proper consideration of any type of data is the establishment of the ”quality” of these data. RESOLVE concentrates on the analysis of statistical significance.

Structuring research data through mathematical models

A main target of RESOLVE is to create mathematical models and related software for the simulation of models with reference to the applications.


Nicola Bellomo
(Politecnico di Torino) - workpackage-leader

José Maria Carazo (Integromics)