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Systems Biology is an approach to biology and medicine that has the potential to lead to a better understanding of how biological properties emerge from the interaction of genes, proteins, molecules, cells and organisms. The approach aims at elucidating how these interactions govern biological function by employing experimental data, mathematical models and computational simulations. As Systems Biology is inherently multidisciplinary, education within this field meets numerous hurdles including departmental barriers, availability of all required expertise locally, appropriate teaching material and example curricula. As university education at the Bachelor’s level is traditionally built upon disciplinary degrees, we believe that the most effective way to implement education in Systems Biology would be at the Master’s level, as it offers a more flexible framework. Our team of experts and active performers of Systems Biology education suggest here (i) a definition of the skills that students should acquire within a Master’s programme in Systems Biology, (ii) a possible basic educational curriculum with flexibility to adjust to different application areas and local research strengths, (iii) a description of possible career paths for students who undergo such an education, (iv) conditions that should improve the recruitment of students to such programmes and (v) mechanisms for collaboration and excellence spreading among education professionals. With the growing interest of industry in applying Systems Biology approaches in their fields, a concerted action between academia and industry is needed to build this expertise. Here we present a reflection of the European situation and expertise, where most of the challenges we discuss are universal, anticipating that our suggestions will be useful internationally. We believe that one of the overriding goals of any Systems Biology education should be a student’s ability to phrase and communicate research questions in such a manner that they can be solved by the integration of experiments and modelling, as well as to communicate and collaborate productively across different experimental and theoretical disciplines in research and development., npj Systems Biology and Applications, 2, ISSN:2056-7189

The dynamics of a proteome can only be addressed with large-scale, high-throughput methods. To cope with the inherent complexity, techniques based on targeted quantification using proteotypic peptides are arising. This is an essential systems biology approach; however, for the exploratory discovery of unexpected markers, nontargeted detection of proteins, and protein modifications is indispensable. We present a rapid label-free shotgun proteomics approach that extracts relevant phenotype-specific peptide product ion spectra in an automated workflow without prior identification. These product ion spectra are subsequently sequenced with database search and de novo prediction algorithms. We analyzed six potato tuber cultivars grown on three plots of two geographically separated fields in Germany. For data mining about 1.5 million spectra from 107 analyses were aligned and statistically examined in approximately 1 day. Several cultivar-specific protein markers were detected. Based on de novo-sequencing a dominant protein polymorphism not detectable in the available EST-databases was assigned exclusively to a specific potato cultivar. The approach is applicable to organisms with unsequenced or incomplete genomes and to the automated extraction of relevant mass spectra that potentially cannot be identified by genome/EST-based search algorithms.

On March 21st, representatives from 26 countries met in Brussels to execute the kick-off meeting of the new COST Action (Cooperation in Science and Technology) CA15110: "Harmonising standardisation strategies to increase efficiency and competitiveness of European lifescience research (CHARME)". The participants exchanged information about the need for understanding formats and standards for biological data and computer models in systems biology research, and elected Chair, Vice Chair and working group leaders.

Molecular medicine is undergoing fundamental changes driving the whole area towards a revolution in modern medicine. The breakthrough was generated the fast-developing technologies in molecular biology since the first draft sequence of the human genome was published. The technological advances enabled the analysis of biological samples from cells and organs to whole organisms in a depth that was not possible before. These technologies are increasingly implemented in the medical and health care system to study diseases and refine diagnostics. As a consequence, the understanding of diseases and the health status of an individual patient is now based on an enormous amount of data that can only be interpreted in the context of the body as a whole. Systems biology as a new field in the life sciences develops new approaches for data integration and interpretation. Systems medicine as a specialized aspect of systems biology combines in an interdisciplinary approach all expertise necessary to decipher the human body in all its complexity. This created new challenges in the area of information and communication technologies to provide the infrastructure and technology needed to cope with the data flood that will accompany the next generation of medicine. The new initiative 'IT Future of Medicine' aims at driving this development even further and integrates not only molecular data (especially genomic information), but also anatomical, physiological, environmental, and lifestyle data in a predictive model approach-the 'virtual patient'-that will allow the clinician or the general practitioner to predict and anticipate the optimal treatment for the individual patient. The application of the virtual patient model will allow truly personalized medicine.

Systems biology requires the availability, co-ordination and simultaneous interaction of a large number of diverse facilities and activities. These cover an entire spectrum, from mathematical modelling, through biological, biomedical and clinical experiments, to dedicated technology development. The systems biology community needs close cooperation with data-generation groups and bioinformaticians to define a strategy for producing life-science data of sufficiently high quality for model generation. For each medical, biological or biotechnological problem addressed, the optimal combination of facilities and activities is likely to be different. The complexity of biological systems, and the diversity and dynamics of their processes, means that a full analysis is far too complex to be handled by a single entity, industry or country – a variety of specialist expertise and facilities are typically necessary to achieve results suitable for modelling. Systems-level approaches for tackling the complexity of life-science data provide a profound conceptual advance compared to reductionist biological research methods of the past. Rather than focusing on individual laboratories, specialising in a limited number of research technologies, the Infrastructure for Systems Biology in Europe (ISBE) will facilitate the synergistic application of a wide range of research techniques and technologies to problems of major medical and biotechnological importance.

Modern life sciences are facing a rapidly increasing amount of data produced worldwide. The diversity and heterogeneity of the data calls for standardized formats for the data itself, its description and its context (the metadata), as well as for the processes during generation and processing of the data, the Standard Operating Procedures (SOPs). The newly established project “NORM-SYS - Normalization and standardization for the exchange of models and data in systems biology research” aims at harmonizing standardization processes for model and data exchange in systems biology.