This book covers trends in modern biotechnology. It treats all aspects of this interdisciplinary technology, where knowledge, methods and expertise are required from chemistry, biochemistry, microbiology, genetics, chemical engineering and computer science.

Individual organisms are de?ned by their genetic code. During development andasaresponsetoexternalstimulithegeneticinformationistranslated into awell-de?nedanswerresultingintheexpressionandmodi?cationofproteins. The processes that control protein-protein interactions (PPI) are presently mostly described in terms of individual protein-protein interactions. In vivo suchinteractions are partof complex molecular interaction networksthat are highlydynamicintimeandspace.Onthebasisofquantitative experiments, it would be possible to understand such complex biological systems leading to anunravelingofthesenetworksandallowingthemtobecaughtinquantitative and predictive models. This textbook illustrates the rise of a relatively new area of biology. The shifting of research from the structural assembly of cells and whole org- isms to metabolic diversity led to the beginning of interactomics. This ?eld hasarisenfromtheincreasingimportanceofmolecularbiologyandbioch- istry in basic research as well as in prognostics and prevention of diseases in connection withbiomarker development. The behavior, morphology, and response to stimuli in biological systems arepredetermined bytheinteractionsbetweentheircomponents.Theseint- actions, as we observe them now, are therefore shaped by genetic variations and selective pressure. With the understanding of molecular interactions the biologyisgettingeasier tosurvey.Thecharacterizationofproteininteractions cancontribute to the understanding ofmany processes in nature. Knowledgeofthedifferenttypesofbiologicalmacromoleculesandincre- ingnumbersofwholegenomicstudiesfacilitatetheelucidationofcellularp- cesses. Whether it is genomics, transcriptomics, proteomics, interactomics, or metabolomics, the full complement of genomic information at different levels can be compared between different organisms to reveal similarities or differences and even to provide consensus models.