Cvijovic Marija, Almquist Joachim, Hagmar Jonas, Hohmann Stefan, Kaltenbach Hans-Michael, Klipp Edda, Krantz Marcus, Mendes Pedro, Nelander Sven, Nielsen Jens, Pagnani Andrea, Przulj Natasa, Raue Andreas, Stelling Jörg, Stoma Szymon, Tobin Frank, Wodke Judith A H, Zecchina Riccardo, Jirstrand Mats
Department of Mathematical Sciences, Chalmers University of Technology and University of Gothenburg, Chalmers Tvärgata 3, 412 96, Göteborg, Sweden,
Mol Genet Genomics. 2014 Oct;289(5):727-34. doi: 10.1007/s00438-014-0843-3. Epub 2014 Apr 13.
Systems biology aims at creating mathematical models, i.e., computational reconstructions of biological systems and processes that will result in a new level of understanding-the elucidation of the basic and presumably conserved "design" and "engineering" principles of biomolecular systems. Thus, systems biology will move biology from a phenomenological to a predictive science. Mathematical modeling of biological networks and processes has already greatly improved our understanding of many cellular processes. However, given the massive amount of qualitative and quantitative data currently produced and number of burning questions in health care and biotechnology needed to be solved is still in its early phases. The field requires novel approaches for abstraction, for modeling bioprocesses that follow different biochemical and biophysical rules, and for combining different modules into larger models that still allow realistic simulation with the computational power available today. We have identified and discussed currently most prominent problems in systems biology: (1) how to bridge different scales of modeling abstraction, (2) how to bridge the gap between topological and mechanistic modeling, and (3) how to bridge the wet and dry laboratory gap. The future success of systems biology largely depends on bridging the recognized gaps.
系统生物学旨在创建数学模型，即对生物系统和过程进行计算重建，这将带来新的理解层面——阐明生物分子系统的基本且可能保守的“设计”和“工程”原理。因此，系统生物学将把生物学从现象学转变为预测性科学。生物网络和过程的数学建模已经极大地增进了我们对许多细胞过程的理解。然而，鉴于目前产生的大量定性和定量数据，以及医疗保健和生物技术中众多亟待解决的重要问题，该领域仍处于早期阶段。该领域需要新颖的方法来进行抽象，对遵循不同生化和生物物理规则的生物过程进行建模，以及将不同模块组合成更大的模型，同时仍能利用当今可用的计算能力进行现实模拟。我们已经识别并讨论了系统生物学目前最突出的问题：（1）如何弥合不同建模抽象层次之间的差距，（2）如何弥合拓扑建模和机制建模之间的差距，以及（3）如何弥合湿实验室和干实验室之间的差距。系统生物学未来的成功很大程度上取决于弥合这些已认识到的差距。
