Department of Computer Science and Engineering, Indian Institute of Technology, Roorkee, IN 247667, USA.
Department of Electrical and Computer Engineering, Duke University, Durham, NC 27701, USA.
Bioinformatics. 2022 Jan 12;38(3):864-865. doi: 10.1093/bioinformatics/btab669.
Studying biological systems generally relies on computational modeling and simulation, e.g., model-driven discovery and hypothesis testing. Progress in standardization efforts led to the development of interrelated file formats to exchange and reuse models in systems biology, such as SBML, the Simulation Experiment Description Markup Language (SED-ML) or the Open Modeling EXchange format. Conducting simulation experiments based on these formats requires efficient and reusable implementations to make them accessible to the broader scientific community and to ensure the reproducibility of the results. The Systems Biology Simulation Core Library (SBSCL) provides interpreters and solvers for these standards as a versatile open-source API in JavaTM. The library simulates even complex bio-models and supports deterministic Ordinary Differential Equations; Stochastic Differential Equations; constraint-based analyses; recent SBML and SED-ML versions; exchange of results, and visualization of in silico experiments; open modeling exchange formats (COMBINE archives); hierarchically structured models; and compatibility with standard testing systems, including the Systems Biology Test Suite and published models from the BioModels and BiGG databases.
SBSCL is freely available at https://draeger-lab.github.io/SBSCL/ and via Maven Central.
Supplementary data are available at Bioinformatics online.
研究生物系统通常依赖于计算建模和模拟,例如,基于模型的发现和假设检验。标准化工作的进展导致了相关文件格式的发展,以便在系统生物学中交换和重用模型,例如 SBML、仿真实验描述标记语言 (SED-ML) 或开放式建模交换格式。基于这些格式进行仿真实验需要高效且可重复使用的实现,以便更广泛的科学界能够访问它们,并确保结果的可重复性。系统生物学仿真核心库 (SBSCL) 提供了这些标准的解释器和求解器,作为 Java 中的多功能开源 API。该库可以模拟甚至复杂的生物模型,并支持确定性常微分方程;随机微分方程;基于约束的分析;最新的 SBML 和 SED-ML 版本;结果交换和计算机实验的可视化;开放式建模交换格式(COMBINE 档案);分层结构模型;以及与标准测试系统的兼容性,包括系统生物学测试套件和来自 BioModels 和 BiGG 数据库的已发布模型。
SBSCL 可在 https://draeger-lab.github.io/SBSCL/ 上免费获得,并通过 Maven Central 获得。
补充数据可在生物信息学在线获得。