School of Fundamental Sciences.
School of Veterinary Science, Massey University, Palmerston North 4442, New Zealand.
Bioinformatics. 2020 May 1;36(9):2938-2940. doi: 10.1093/bioinformatics/btaa002.
We present sismonr, an R package for an integral generation and simulation of in silico biological systems. The package generates gene regulatory networks, which include protein-coding and non-coding genes along with different transcriptional and post-transcriptional regulations. The effect of genetic mutations on the system behaviour is accounted for via the simulation of genetically different in silico individuals. The ploidy of the system is not restricted to the usual haploid or diploid situations but can be defined by the user to higher ploidies. A choice of stochastic simulation algorithms allows us to simulate the expression profiles of the genes in the in silico system. We illustrate the use of sismonr by simulating the anthocyanin biosynthesis regulation pathway for three genetically distinct in silico plants.
The sismonr package is implemented in R and Julia and is publicly available on the CRAN repository (https://CRAN.R-project.org/package=sismonr). A detailed tutorial is available from GitHub at https://oliviaab.github.io/sismonr/.
Supplementary data are available at Bioinformatics online.
我们介绍了 sismonr，这是一个用于综合生成和模拟生物信息系统的 R 包。该包生成基因调控网络，包括编码蛋白和非编码基因，以及不同的转录和转录后调控。通过模拟遗传上不同的生物信息个体，考虑了遗传突变对系统行为的影响。系统的倍性不受通常的单倍体或二倍体情况的限制，而是可以由用户定义为更高的倍性。选择随机模拟算法可以让我们模拟生物信息系统中基因的表达谱。我们通过模拟三种遗传上不同的生物信息植物的花色素生物合成调控途径来说明 sismonr 的使用。
sismonr 包是用 R 和 Julia 实现的，并在 CRAN 存储库（https://CRAN.R-project.org/package=sismonr）上公开可用。详细的教程可在 GitHub 上获得，网址为 https://oliviaab.github.io/sismonr/。
补充数据可在生物信息学在线获得。
