MUFINS: multi-formalism interaction network simulator.
MUFINS: multi-formalism interaction network simulator.
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DOI：
10.1038/npjsba.2016.32
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发表时间：
2016
影响因子：
4
通讯作者：
Kierzek AM
中科院分区：
文献类型：
--
作者：
Wu H;von Kamp A;Leoncikas V;Mori W;Sahin N;Gevorgyan A;Linley C;Grabowski M;Mannan AA;Stoy N;Stewart GR;Ward LT;Lewis DJM;Sroka J;Matsuno H;Klamt S;Westerhoff HV;McFadden J;Plant NJ;Kierzek AM
系统生物学已经建立了许多方法，用于细胞中分子网络的机制建模和遗留模型。目前的前沿是整合模型表达在不同的形式主义，以解决多尺度生物系统组织的挑战。我们提出了MUFINS（多形式主义交互网络模拟器）软件，实现了一套独特的交互网络多形式主义模拟方法。我们扩展了基于约束的建模（CBM）的框架，通过纳入线性抑制约束，使第一次线性建模的网络同时描述基因调控，信号传导和稳态下的全细胞代谢。我们提出了一个用例，其中调控网络的逻辑超图模型由线性约束表示，并与小鼠巨噬细胞的基因组规模代谢网络（GSMN）集成。我们通过实验验证预测，展示了我们的软件在假设生成，验证和模型改进的迭代周期中的应用。MUFINS采用了我们的准稳态Petri网方法的扩展版本，将动态模型与CBM相结合，我们通过与人类Recon2 GSMN集成的皮质醇信号传导的动态模型和生理隔室中的营养动态模型来证明这一点。最后，我们实现了一些方法，用于从组学数据中获得代谢状态，包括我们的iMAT一致性方法的新变体。我们通过分析262个个体肿瘤转录组，将我们的方法与iMAT进行了比较，恢复了癌症中代谢重编程的特征。该软件提供了具有网络可视化的图形用户界面，便于在编码和数学建模环境中没有经验的研究人员使用。
Systems Biology has established numerous approaches for mechanistic modeling of molecular networks in the cell and a legacy of models. The current frontier is the integration of models expressed in different formalisms to address the multi-scale biological system organization challenge. We present MUFINS (MUlti-Formalism Interaction Network Simulator) software, implementing a unique set of approaches for multi-formalism simulation of interaction networks. We extend the constraint-based modeling (CBM) framework by incorporation of linear inhibition constraints, enabling for the first time linear modeling of networks simultaneously describing gene regulation, signaling and whole-cell metabolism at steady state. We present a use case where a logical hypergraph model of a regulatory network is expressed by linear constraints and integrated with a Genome-Scale Metabolic Network (GSMN) of mouse macrophage. We experimentally validate predictions, demonstrating application of our software in an iterative cycle of hypothesis generation, validation and model refinement. MUFINS incorporates an extended version of our Quasi-Steady State Petri Net approach to integrate dynamic models with CBM, which we demonstrate through a dynamic model of cortisol signaling integrated with the human Recon2 GSMN and a model of nutrient dynamics in physiological compartments. Finally, we implement a number of methods for deriving metabolic states from ~omics data, including our new variant of the iMAT congruency approach. We compare our approach with iMAT through the analysis of 262 individual tumor transcriptomes, recovering features of metabolic reprogramming in cancer. The software provides graphics user interface with network visualization, which facilitates use by researchers who are not experienced in coding and mathematical modeling environments.
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DOI：
10.1093/bioinformatics/btt552
发表时间：
2013-12-15
期刊：
Bioinformatics (Oxford, England)
影响因子：
--
作者：
Fisher CP;Plant NJ;Moore JB;Kierzek AM
通讯作者：
Kierzek AM
影响因子：
5.8
作者：
Hucka, M;Finney, A;Wang, J
通讯作者：
Wang, J
影响因子：
9.5
作者：
Breitling, Rainer;Gilbert, David;Orton, Richard
通讯作者：
Orton, Richard
影响因子：
--
作者：
Diamant, Idit;Eldar, Yonina C.;Shlomi, Tomer
通讯作者：
Shlomi, Tomer
影响因子：
64.8
作者：
Curtis, Christina;Shah, Sohrab P.;Chin, Suet-Feung;Turashvili, Gulisa;Rueda, Oscar M.;Dunning, Mark J.;Speed, Doug;Lynch, Andy G.;Samarajiwa, Shamith;Yuan, Yinyin;Graef, Stefan;Ha, Gavin;Haffari, Gholamreza;Bashashati, Ali;Russell, Roslin;McKinney, Steven;Langerod, Anita;Green, Andrew;Provenzano, Elena;Wishart, Gordon;Pinder, Sarah;Watson, Peter;Markowetz, Florian;Murphy, Leigh;Ellis, Ian;Purushotham, Arnie;Borresen-Dale, Anne-Lise;Brenton, James D.;Tavare, Simon;Caldas, Carlos;Aparicio, Samuel
通讯作者：
Aparicio, Samuel