Department of Signal Processing, Tampere University of Technology, 33101 Tampere, Finland.
Bioinformatics. 2012 Nov 15;28(22):3004-5. doi: 10.1093/bioinformatics/bts556. Epub 2012 Sep 26.
Cell growth and division affect the kinetics of internal cellular processes and the phenotype diversity of cell populations. Since the effects are complex, e.g. different cellular components are partitioned differently in cell division, to account for them in silico, one needs to simulate these processes in great detail.
We present SGNS2, a simulator of chemical reaction systems according to the Stochastic Simulation Algorithm with multi-delayed reactions within hierarchical, interlinked compartments which can be created, destroyed and divided at runtime. In division, molecules are randomly segregated into the daughter cells following a specified distribution corresponding to one of several partitioning schemes, applicable on a per-molecule-type basis. We exemplify its use with six models including a stochastic model of the disposal mechanism of unwanted protein aggregates in Escherichia coli, a model of phenotypic diversity in populations with different levels of synchrony, a model of a bacteriophage's infection of a cell population and a model of prokaryotic gene expression at the nucleotide and codon levels.
SGNS2, instructions and examples available at www.cs.tut.fi/~lloydpri/sgns2/ (open source under New BSD license).
Supplementary data are available at Bioinformatics online.
细胞的生长和分裂会影响内部细胞过程的动力学和细胞群体的表型多样性。由于这些影响很复杂,例如在细胞分裂中不同的细胞成分会以不同的方式分配,因此需要在计算机中模拟这些过程。
我们提出了 SGNS2,这是一种根据具有多层次、相互关联的隔间中的多延迟反应的随机模拟算法来模拟化学反应系统的模拟器,这些隔间可以在运行时创建、销毁和分割。在分裂过程中,分子根据与几种分配方案之一对应的指定分布随机分配到子细胞中,这些方案可以基于每个分子类型应用。我们用六个模型来说明其用法,包括大肠杆菌中不需要的蛋白质聚集体处理机制的随机模型、具有不同同步水平的群体的表型多样性模型、噬菌体感染细胞群体的模型和原核生物在核苷酸和密码子水平上的基因表达模型。
SGNS2、说明和示例可在 www.cs.tut.fi/~lloydpri/sgns2/ 获得(根据新 BSD 许可证开源)。
补充数据可在 Bioinformatics 在线获得。