In a 2002 Nature paper systems biology was defined as the “mathematical concepts […] to illuminate the principles underlying biology at a genetic, molecular, cellular and even organismal level” (Surridge, 2002, p. 205). During the past years these mathematical concepts have become ‘whole-cell simulations’ in order to observe and understand the complex dynamic behavior of cells. Already in 1997 the very first minimal cell was created in-silico, called the ‘virtual self-surviving cell (SSC)’, consisting of 120 in-silico synthesized genes of the 480 genes of M. genitalium and 7 genes from other species (Tomita, 2001). The virtual self-surviving cell absorbs up and metabolizes glucose, and generates ATP as an energy source for protein and membrane synthesis. SSC allows to observe the changes in the amount of substances inside the cell as well as the gene expression resulting from these changes, to study the temporal patterns of change, and, finally, to conduct experiments, e.g. real-time gene knock-out experiments.

However, the situation of modeling and simulation in cell biology is characterized by a wide variety of modeling practices and methods. There are thousands of simple models around, an increasing amount of simulations for more complex models, and various computational tools to ease modeling. Furthermore, quantitative data for initializing simulation runs are lacking. Thus, in order to establish a simulation-oriented biology, advanced methods of standardization and quantification are required. The release of the Systems Biology Markup Language (SBML) in 2003 and the Systems Biology Graphical Notation (SBGN) in 2009 are examples of such efforts for standardization as well as the development of time-based measurements, e.g. of high-throughput technologies for measuring changes in inner-cellular metabolites. The paper will first present an overview of the past developments for advancing standardization and quantification for ‘whole-cell simulations’. It will present the case of the E-Cell project (including the SSC) of the Laboratory for Bioinformatics at Keio University, initiated by Masaru Tomita. E-Cell not only aimed from very early on “to develop the theories, techniques, and software platforms necessary for whole-cell-scale modeling, simulation, and analysis,” (Takahashi et al., 2002, p. 64) but also strengthened the required infrastructure “for this new type of simulation-orientated biology, [… by establishing] three centers for metabolome research, bioinformatics, and genome engineering, respectively” in 2001 (Tomita, 2001, p. 2). The paper, finally, will evaluate these developments from today’s perspective.