Mol Syst Biol. 1: 2005.0007 Creating comprehensive models that can predict cellular behaviors is one of the major goals of systems biology. This requires the integration of experimental, computational, and theoretical approaches. Molecular interactions have to be precisely described in mathematical formula that reflects the right level of abstraction suitable for specific biology, and the necessary parameters, such as initial concentration of each component and kinetic constants, have to be estimated from a set of experiments. Although abundant experimental data and published articles are available, creating a quality model by assembling these resources is undesirable as each data set is based on an experiment with a different setup. There is serious need to obtain consistent and comprehensive data measuring different aspects of the focused system so that it can be a basis for quantitative modeling. The problem is that it requires a broad range of expertise and resources, often beyond the capability of a single research group, or even beyond the institution. For example, a particular research group may be able to carry out expression profiles; however, the group may not have the expertise to run image‐based time‐lapse quantitative localization assays. An experimental group does not necessarily have the computational resources required for modeling. This has led to the establishment of a number of interdisciplinary research groups with extensive networks of collaboration. Collaborations among groups have been common practice in the research community. The major difference in recent collaborations is that of scale leading to self‐organization of global alliances to tackle biological complexity. The recent success of global alliance in biology is signified by the human genome project. The emerging alliance requires quite a different approach. In the human genome project, the main issue was how to efficiently and accurately sequence the genome, so the challenge has been quite …