Departamento de Biología Molecular y Bioquímica, Facultad de Ciencias, Universidad de Málaga, E-29071 Málaga, and CIBER de Enfermedades Raras (CIBERER), Málaga, Spain.
ICREA-Complex Systems Lab, Universitat Pompeu Fabra. Parc de Recerca Biomèdica de Barcelona. Dr. Aiguader 88, 08003. Barcelona, Spain.
Bioessays. 2010 Mar;32(3):246-256. doi: 10.1002/bies.200900145.
The search for a systems-level picture of metabolism as a web of molecular interactions provides a paradigmatic example of how the methods used to characterize a system can bias the interpretation of its functional meaning. Metabolic maps have been analyzed using novel techniques from network theory, revealing some non-trivial, functionally relevant properties. These include a small-world structure and hierarchical modularity. However, as discussed here, some of these properties might actually result from an inappropriate way of defining network interactions. Starting from the so-called bipartite organization of metabolism, where the two meaningful subsets (reactions and metabolites) are considered, most current works use only one of the subsets by means of so-called graph projections. Unfortunately, projected graphs often ignore relevant biological and chemical constraints, thus leading to statistical artifacts. Some of these drawbacks and alternative approaches need to be properly addressed.
寻找代谢作为分子相互作用网络的系统级图景为我们提供了一个典范的例子,说明了用于描述系统的方法如何会影响对其功能意义的解释。代谢图谱已经使用网络理论的新方法进行了分析,揭示了一些非平凡的、与功能相关的特性。这些特性包括小世界结构和层次模块化。然而,正如这里所讨论的,其中一些特性实际上可能是由于定义网络相互作用的不当方式所致。从代谢的所谓二分组织开始,其中两个有意义的子集(反应和代谢物)被考虑在内,目前大多数的工作仅使用所谓的图投影的子集之一。不幸的是,投影图往往忽略了相关的生物和化学约束,从而导致统计伪影。需要正确解决其中的一些缺点和替代方法。