NISB Research Strategy

Premise

Research projects within NISB research projects are characterised by an intimate and iterative combination of experimental (‘wet’) and modelling (‘dry’) activities. Choices in ‘wet’ research are ideally driven by quantitative and predictive bio-modelling. At the same time, ‘dry’ research will be devoted to develop generic and specific bio-modelling approaches and theories, based on experimental data sets. This approach allows full implementation of the systems biology paradigm, initiating and exploiting the iterative cycle, and ensures a systematic, goal-oriented and efficient tackling of key problems in the life sciences.
NISB starts from the notion that underlying principles are highly similar in all organisms, from ‘simple’ unicellular prokaryotes to multicellular higher eukaryotes, including animals and plants. Because the systems biology type of approach requires large and diverse experimental data sets, NISB will focus on a small number of experimental systems in parallel, exploiting the benefits from each and combining the insights obtained.
NISB focuses on the integrated functioning of metabolic, signal-transduction and genetic networks in combination with systems that drive the generation of shape and force in living cells.

Objectives

NISB aims to coordinate and share research efforts, research facilities, knowledge, and grant applications on behalf of its partners.
NISB is set to achieve the following objectives:
- Amalgamating and strengthening research in the field of molecular systems biology by combining and synergising expertise in biology, biophysics, computational sciences and engineering by initiating and executing collaborative research programs;
- Develop and foster scientific excellence in the national and international field of system biology;
- Enhance our scientific strength to be successful on the highly dynamic national and European funding markets.
Thus, NISB practices as a group the same principle as underscores its science: components (i.e. partners/researchers) can only achieve their full potential when operating in the context of a network/system.

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