Description
Scitus Academics Systems Biology-Scitus by Ian Vernon, Martin Zwick
Interest in systems biology has increased rapidly in the past decade, as evidenced by the number of referencing publications. Systems biology has fuzzy boundaries and overlaps with several emerging, post-genomic fields, such as synthetic biology, systems microbiology, systems biotechnology, integrative biology, systems biomedicine, and metagenomics. The motive of systems biology is the modeling and discovery of emergent properties of a system whose theoretical description is only possible only by using systems biology technology. These generally involve cell signaling networks. Systems biology has its roots in the quantitative modeling of enzyme kinetics, mathematical modeling of population growth and the simulations developed to study neurophysiology, control theory and cybernetics. The inevitable role bioinformatics plays in modern systems biology puts mathematical and computational sciences as an equal partner to analytical and experimental biology. Furthermore, mathematical and computational models are expected to become increasingly prevalent representations of our knowledge about specific biochemical systems.
Systems Biology covers experimental and theoretical aspects of the function of biological systems at the molecular, cellular or organismal level, in particular those addressing the engineering of biological systems; network modelling, quantitative analyses, integration of different levels of information and synthetic biology. As biological research accelerates through the development of new technologies and instrumentation, biological databases have become an indispensable partner in such research. Building and maintaining of primary databases such as GenBank or Protein Data Bank have long been recognized as important bioinformatics work. Therefore, these “systems biology databases” often represent important foundations for quantitative modeling of biological systems.