Systems biology

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Systems biology approach.

The Systems Biology (synonym: Systeomik , English systems biology , integrative biology or predictive biology ) is a branch of biological sciences that attempts to biological organisms to understand in its entirety.

The aim is to get an integrated picture of all regulatory processes at all levels from the genome to the proteome to the organelles to the behavior and biomechanics of the entire organism. Essential methods for this purpose come from systems theory and its sub-areas. However, since the mathematical-analytical side of systems biology is not perfect, computer simulations and heuristics are often used as research methods .

Systems biology reintroduces time as an important factor in molecular biology . So far, this has avoided thinking about the exact timing of reactions; quite in contrast to biochemistry . Systems biology returns to the biochemical view of the world, thinking about processes and how they change over time, but with a radical expansion of the scale. Thousands of reactants are observed in systems biology, which results in systems biology in a much more dynamic view of biology than that of classical molecular biology or genetics .


  • Systems biology does not examine individual genes or proteins at a specific point in time, as has been successfully practiced for the past 30 years. It studies the behavior and relationship of all elements in a given biological system while it is functioning.
  • To understand biology on a systemic level, it is necessary to study the structure and dynamics of cellular functions as well as the functions of the organism and not the properties of isolated parts of a cell or an organism.
  • Systems biology tries to quantitatively predict the behavior of a biological process that has been exposed to disturbances, so that this quantitative method bases its strength on the explicit inclusion of the components involved in the process, their interactions and realistic values ​​of their concentrations, locations and states.
  • A discipline at the intersection of biology , mathematics and physics which combines experimental and computational approaches to understand biological processes in cells, tissues and organisms.
  • Systems biology aims to achieve a comprehensive quantitative understanding of the dynamic interactions between the building blocks and components of a biological system in order to understand the behavior of the system as a whole and to enable predictions. To achieve this goal, mathematical concepts are applied to biological systems. An interactive process between laboratory experiment and modeling in the computer is of central importance here.


  • The concept of integrative studies of biological systems is not new. A biological sub-area in which systems analysis has been carried out for several decades is ecology . The famous Lotka-Volterra equation from 1931 can already be seen as a systemic approach.
  • The importance of systems biology was recognized by Norbert Wiener in 1948 .
  • The British neurophysiologists and Nobel Prize winners Alan Lloyd Hodgkin and Andrew Fielding Huxley are considered pioneers in systems biology, who laid the foundations for the mathematical simulation of life processes on the basis of differential equations with the mathematical model of a nerve cell in 1952 .
Andrew Huxley, July 2005
  • In 1960 Denis Noble caused a sensation with the publication of his doctoral thesis in the journal Nature ; In it he presented the first mathematical model of a beating heart, with which new drugs and defibrillation devices can be tested on the computer.
  • The term systems biology has been in use since the 1960s; originally in connection with dynamic interactions, mathematical modeling and simulation of biological signal pathways.
  • The breakthrough for systems biology came at the turn of the millennium with the development of high-throughput technologies for measuring gene expression, protein expression and protein-protein interaction at the molecular level and the completion of the human genome project and numerous other genome projects. The flood of data obtained for around three billion base pairs and over a million proteins per cell makes it impossible to carry out all theoretically conceivable and interesting experiments in the laboratory. Therefore, modeling on the computer has become a prerequisite for selecting the most promising approaches.

The widespread use of the Internet was a basic requirement for the breakthrough in systems biology, as it was only then that the joint use of huge amounts of data in international cooperation was made possible.

The current state of science can be found in specialized journals such as Molecular Systems Biology, as well as at numerous international congresses such as B. the ICSB.

Methodical approaches

Schematic representation of the systems biological approach

A systems biology approach includes repetitive cycles of experiments and hypothesis-driven modeling :

  1. A complete characterization of the essential components of an organism , such as its molecules and their interaction and how these interactions regulate the function of the cell.
  2. Analysis of the reactions of an organism to disorders such as deletion or overexpression of genes, changes in growth conditions or stimulation with hormones .
  3. A temporal and spatial characterization of the cells , e.g. B. their compartmentalization , vesicular transport and dynamics of the different components.
  4. The information obtained is then translated into mathematical models in order to test the knowledge gained and to formulate hypotheses and, if necessary, to improve the model based on the experimentally gained knowledge.

These mathematical models can be used to predict the behavior of a system under certain conditions and ultimately develop new strategies to manipulate and control cells, which can ultimately lead to the development of new drugs.

Basically one differentiates

  1. Top-down approach: In the research branches of ' omics ' such as genomics , proteomics , toponomics , transcriptomics , metabolomics , glycomics , interactomics , intergenomics and fluxomics , the top-down approach has proven to be the predominant method of choice. The top-down approach starts with the " bird's eye view ", i. In other words, experimental data are first generated and collected using high-throughput methods, and then an attempt is made to discover and characterize biological mechanisms in these data. The main goal of the top-down approach is to discover new molecular mechanisms by analyzing experimental data and formulating hypotheses, which in turn are tested by experiments.
  2. Bottom-up approach: The bottom-up approach determines the properties of an already characterized subsystem by describing the interactions of each component. These mathematical models are then used to predict the behavior of each system. The aim of this second approach is to combine the various metabolic pathways into a model of the whole system with the ultimate goal of synthetic biology . Bottom-up approaches require:
    1. Detailed information about the kinetic and physicochemical properties of the individual components involved.
    2. Detailed data on the system's response to external stimuli.
    3. Detailed computer models to test hypotheses, improve the model and make predictions.
    4. Development of tools for the representation and analysis of the generated models.

The philosophy of science is currently discussing the extent to which the philosophy of physics can be transferred to that of systems biology. Obviously, the research field of systems biology is an extension of classical molecular biology with mathematical methods. Since mathematical modeling plays a similarly large role in systems biology as in physics, it was initially thought that the epistemology on which physics is based could be transferred to systems biology. However, systems biology lacks universal theories such as general relativity or Maxwell's basic equations of electrodynamics. It therefore seems necessary to develop your own philosophy of systems biology.

Math and modeling

Both approaches are based on differential equations that describe the change in biological phenomena at a specific point in time t. So z. B. the membrane potential of a nerve cell according to the Hodgkin-Huxley model u. a. as a function of the ion currents of potassium and sodium :


Examples of systems biology

  • Principles of bacterial signal networks :

Biochemical networks in cells have to function reliably in a chaotic environment with imperfect components. In 2005, Markus Kollman and colleagues were able to show through a combination of experiments and computer modeling that Escherichia coli has the smallest, sufficiently robust chemotactic system, which allows a precise chemotactic response of the organism while minimizing the costs for the organism.

Scientists have long been fascinated by the even distribution of hair follicles. Using a reaction diffusion model, Sick and colleagues were able to show that the protein WNK and its inhibitor DKK can increase the density of the hair follicles and that other signal transduction pathways are also involved in the distribution pattern of the hair follicles.

The JAK-STAT signaling pathway is involved in many pathways of lying at the cell surface receptors such. B. the one for Epo involved. Using mathematical modeling of the JAK-STAT signaling pathway , Swameye I. and colleagues were able to show that the STAT5 protein , which was not directly accessible to experimental measurements, is periodically transported from the cell nucleus to the cytoplasm and back. The fact that the two isoforms STAT5A and STAT5B randomly form homo- and heterodimers in the course of the activation of STAT5 and that these have different retention times in the cell nucleus after their translocation could later also be shown in a systems biology approach using mathematical modeling by Böhm ME and colleagues.

Funding projects


Systems biology and its method development are sustainably funded by the EU within the 6th and 7th framework program. The Federal Ministry of Education and Research (BMBF) has been promoting systems biology since 2004 as part of the HepatoSys research project (Competence Network Systems Biology of Hepatocytes).

Since January 2007, the BMBF has been promoting German systems biology with the funding program “Biotechnology - Using and Shaping Opportunities” FORSYS (Research Units of Systems Biology FORSYS) with four centers for systems biology. The four FORSYS centers are located in Freiburg im Breisgau (FRISYS - Freiburg Initiative for Systems Biology, Spokesperson: Wolfgang R. Hess ), Heidelberg (VIROQUANT - Systems Biology of Virus-Cell Interactions), Potsdam (GoFORSYS) and Magdeburg (in cooperation with the Max Planck Institute for Dynamics of Complex Technical Systems ). FORSYS is designed as a “beacon of German systems biology” and is being further expanded with the program “Partner of the Research Units Systems Biology - FORSYS Partner”. Another large network of research projects has been funded by the Helmholtz Association since 2007 . The "Helmholtz Systems Biology Alliance" is primarily concerned with researching the causes of complex diseases. The Helmholtz centers DKFZ , FZJ , HZI , GSF , MDC and UFZ are involved in it. In addition to scientists from the Helmholtz Association, a large number of external cooperation partners are funded.


SysMO ("Systems Biology of Microorganisms" or "Systems Biology of Microorganisms") is a transnational research funding initiative that is being jointly launched by the Federal Ministry of Education and Research and the Federal Ministry of Education, Science and Culture in Austria , the Netherlands Organization for Scientific Research, the Science Council of Norway , the Ministry of Education and Science in Spain and the Science Council for Biotechnology and Biological Research in Great Britain . The aim of SysMO is to establish a systems biology of single-cell microorganisms. From Austria 2, from Germany 29, from Norway 7, from Spain 9, from the Netherlands 15, from Great Britain 22, from the Czech Republic 1, from France 2 and from Switzerland 4 groups are part of the SysMO initiative.


The Nobel laureate and biologist Sydney Brenner characterized the subject in a paper as "low input, high throughput, no output science."

See also



  • Wolfgang Wiechert: Systems Biology - An Interdisciplinary Challenge. Schöningh, Paderborn 2004, ISBN 3-506-72876-8 .
  • Andreas Kremling: Compendium Systems Biology - Mathematical Modeling and Model Analysis. Vieweg + Teubner, 2011, ISBN 978-3-8348-1907-9 .
  • Detlef Weinich: Systems Biology - Dynamics and Interrelations as Research Subject . Roots and meaning of network thinking in the more recent understanding of science. In: Würzburg medical history reports. 21, 2002, pp. 473-489.


Web links

Commons : Systems Biology  - collection of images, videos and audio files

Individual evidence

  1. ^ Stefan Schuster , Roland Eils, Klaus Prank: 5th International Conference on Systems Biology (ICSB 2004), Heidelberg, October 9-13, 2004. In: Biosystems. Volume 83, No. 2-3, February-March 2006, pp. 71-74.
  2. T. Ideker, T. Galitski, L. Hood: A new approach to decoding life: Systems Biology. In: Annu. Rev. Genomics Hum. Genet. 2, p. 343.
  3. H. Kitano: Computational systems biology. In: Nature. 420, 2002, p. 206.
  4. J. Anderson: The National Institute of General Medical Sciences at NIH. 2003.
  5. T. Ideker, LR Winslow, DA Lauffenburger: Bioengineering and systems biology. In: Ann Biomed Eng. 34 (2), Feb 2006, pp. 257-264.
  6. ^ The National Institute of General Medical Sciences at NIH: National Centers for Systems Biology . 2007.
  7. ^ V. Volterra: Leçon sur la théorie mathématique de la lutte pour la vie. Gauthier-Villars, Paris 1931.
  8. ^ Norbert Wiener: Cybernetics or Control and Communication in the Animal and the Machine. The MIT Press, Cambridge, MA 1961.
  9. AL Hodgkin, AF Huxley: A quantitative description of membrane current and its application to conduction and excitation in nerve. In: J Physiol . 117, 1952, pp. 500-544. PMID 12991237 .
  10. ^ D. Noble: Cardiac action and pacemaker potentials based on the Hodgkin-Huxley equations . In: Nature . 188, 1960, pp. 495-497.
  11. ^ O. Wolkenhauer, U. Klingmüller: Systems Biology: From a Buzzword to a Life Sciences Approach. In: BIOforum Europe. 04/2004, Git Verlag, Darmstadt, pp. 22-23.
  12. J. Monod: Le Hasard et la necessitté. Seuil, Paris 1970.
  13. ^ FJ Bruggemann, HV Westerhoff: The nature of systems biology. In: Trends in Microbiology. Vol. 15 no. 1.
  14. M. Kollmann, K. Bartholome, L. Lovdok, J. Timmer, V. Sourjik: Design principles of a bacterial signaling network. In: Nature. 438, 2005, pp. 504-507.
  15. ^ S. Sick, S. Reinker, J. Timmer, T. Schlake: WNT and DKK determine hair follicle spacing through a reaction-diffusion mechanism. In: Science . 314, 2006, pp. 1447-1450.
  16. I. Swameye, TG Müller, J. Timmer, O. Sandra, U. Klingmüller: Identification of nucleocytoplasmic cycling as a remote sensor in cellular signaling by data-based modeling. In: Proc. Natl. Acad. Sci. 100, 2003, pp. 1028-1033.
  17. ^ ME Böhm, L. Adlung, M. Schilling, S. Roth, U. Klingmüller, WD Lehmann: Identification of Isoform-Specific Dynamics in Phosphorylation-Dependent STAT5 Dimerization by Quantitative Mass Spectrometry and Mathematical Modeling. In: J Proteome Res. 13, 2014, pp. 5685-5569. PMID 25333863
  18. ^ Announcement of the BMBF
  19. ^ Errol C. Friedberg: Sydney Brenner. In: Nature Reviews Molecular Cell Biology . 9, 2008, pp. 8-9, doi: 10.1038 / nrm2320 .