Publisher Summary This introductory chapter presents an overview of systems biology, which can be described as a discipline that seeks to quantify and annotate complexity in biological systems to construct algorithmic models with which to predict outcomes from component input. Systems biomedicine is an extension of these strategies into the study of biomedical problems. Medicine is becoming amenable to complexity analysis. The understanding of the cell and molecular biology of human disease has dramatically advanced in the past years. The current systems biology now focuses on complexity and the fundamental unit of study resides in the DNA sequence. In all aspects—biological and mathematical—the greatest advance has been the availability of computational capabilities that can match the systems complexity. This reliance on these genomic and computational technologies and datasets that can be transmuted across species has broadened significantly the applicability of systems approaches to very complex systems such as human medicine. Clearly, the human genome and proteome are more complex than those of yeast and bacteria, and human genetic studies are more complex than those in mice. The complexity of a multicellular and multiorgan system has yet to be configured into the equation. In the final analysis, systems biomedicine will be a significant endeavor. So any increment in improvement in prediction will help medicine and benefit society. The challenges, however, are logistical, computational, and organizational.