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June 2009 No. 4 NEWSLETTER OF FEMS

FEDERATION OF EUROPEAN MICROBIOLOGICAL SOCIETIES

Systems biologyComplexity explained Systems biology. A hot topic in contemporary science gaining ever-increasing attention. In order to address the role of systems biology in general and in microbiology, FEMS Focus interviewed two major personalities in the field – Professor Roel van Driel and Professor Víctor de Lorenzo. Dr. van Driel is the Director of the Netherlands Institute for Systems Biology (NISB) in Amsterdam, The Netherlands and a professor of Biochemistry. Dr. De Lorenzo is the Head of the Systems & Synthetics Biotechnology Program of the National Centre of Biotechnology in Madrid, Spain. Read on for their general views on systems biology, the interface between systems biology and microbiology and the challenges that these novel opportunities should address. What is “systems biology”? NISB Chief Roel van Driel defines systems biology as an approach based on integrative experimental data unified in a single quantitative and predictive mathematical model. This basis of information warrants a goal-oriented and cost-effective analysis, with

which the predictive model is used to identify the best experiments to reach specific goals. To understand complex systems, the iterative cycle of modeldriven experiments and experimental data-driven modeling allows systematic analysis of the underlying principles and logic of complex biomedical systems.

Prof. Dr. Roel van Driel, PhD, is a professor of Biochemistry, Head of the Nuclear Organisation Group (NOG) in the University of Amsterdam (www.uva-nucleus.nl) and the Director of the Netherlands Institute for Systems Biology (NISB) in Amsterdam, The Netherlands (www.sysbio.nl) NISB includes two universities, one physics institute and one mathematics institute. It also has excellent national and international network and numerous collaborations. NISB aims to achieve a synergistic effect by combining and sharing knowledge, research efforts and facilities available at its partners. It practices as a group the same principle as underscores its science: components (i.e. partners) can only achieve their full potential when operating in the context of a network system (i.e. NISB). About 50 % of the x groups included in NISB work on systems biology in microbiology. However, Dr. Van Driel also claims that when one asks 3 persons to define systems biology, one gets 5 answers. Research in NISB is based on the synergism between experimental (‘wet’) and modeling (‘dry’) research, with the aim of developing generic tools in systems biology. Choices in ‘wet’ research are driven by quantitative and predictive bio-modPrinciple of systems biology

From the Editorial Team In this issue of FEMS Focus, we will closein on a topic which enables complicated matters to be addressed – Systems Biology. This field of science is rapidly emerging and gaining importance due to the limited knowledge on how to handle complex data. Systems biology is an interdisciplinary field that focuses on the systematic study of complex interactions in a large context, thus, using a holistic perspective rather than reductionism. With the use of systems biology, new emergent properties that may arise from the systemic view used in this discipline may be discovered and the entirety of processes that happen in a biological system may be better understood. This time, FEMS Focus will address the interface between microbiology and systems biology – “Complexity explained!” Tone Tønjum, Editor & Chared Verschuur, Communications Assistant

eling. At the same time, ‘dry’ research is devoted to develop generic and specific bio-modeling approaches and theories, based on experimental data sets. This approach allows full implementation of the systems biology paradigm, initiating and exploiting the iterative cycle of experiments that can be accumulated into predictive models. Quantitative and mathematical models can be employed to test the working hypothesis and the cycle of new quantitative prediction and experimental verification in a systematic manner (including many components in time and space) can generate an improved model. This approach demands large computational force and ensures a systematic and efficient tackling of key problems in life sciences. NISB concentrates on issues that are central in molecular and cellular life sciences, but has not been addressed systematically yet, namely, the integrated functioning of metabolic, signal transduction and genetic networks in combination with systems that drive the generation of


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