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Systems biology is a rapidly expanding field of research and is applied in a number of biological disciplines. In animal sciences, omics approaches are increasingly used, yielding vast amounts of data, but systems biology approaches to extract understanding from these data of biological processes and animal traits are not yet frequently used. This paper aims to explain what systems biology is and which areas of animal sciences could benefit from systems biology approaches. Systems biology aims to understand whole biological systems working as a unit, rather than investigating their individual components. Therefore, systems biology can be considered a holistic approach, as opposed to reductionism. The recently developed 'omics' technologies enable biological sciences to characterize the molecular components of life with ever increasing speed, yielding vast amounts of data. However, biological functions do not follow from the simple addition of the properties of system components, but rather arise from the dynamic interactions of these components. Systems biology combines statistics, bioinformatics and mathematical modeling to integrate and analyze large amounts of data in order to extract a better understanding of the biology from these huge data sets and to predict the behavior of biological systems. A 'system' approach and mathematical modeling in biological sciences are not new in itself, as they were used in biochemistry, physiology and genetics long before the name systems biology was coined. However, the present combination of mass biological data and of computational and modeling tools is unprecedented and truly represents a major paradigm shift in biology. Significant advances have been made using systems biology approaches, especially in the field of bacterial and eukaryotic cells and in human medicine. Similarly, progress is being made with 'system approaches' in animal sciences, providing exciting opportunities to predict and modulate animal traits.
570, [SDV.BA] Life Sciences [q-bio]/Animal biology, salmonella, animal traits, SF1-1100, dairy-cows, disease, fat synthesis, [SDV.BA]Life Sciences [q-bio]/Animal biology, dairy cow, system biology, mathematical modeling, systems biology, gene-expression, infection, Animal culture, networks, network, physiology, gene expression, responses, animal trait, mathematical model, mathematical-model
570, [SDV.BA] Life Sciences [q-bio]/Animal biology, salmonella, animal traits, SF1-1100, dairy-cows, disease, fat synthesis, [SDV.BA]Life Sciences [q-bio]/Animal biology, dairy cow, system biology, mathematical modeling, systems biology, gene-expression, infection, Animal culture, networks, network, physiology, gene expression, responses, animal trait, mathematical model, mathematical-model
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| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
