GenSSI 2.0: multi-experiment structural identifiability analysis of SBML models

被引：79

作者：

Ligon, Thomas S. ^{[1
,2
]}

Frohlich, Fabian ^{[3
,4
]}

Chis, Oana T. ^{[5
]}

Banga, Julio R. ^{[6
]}

Balsa-Canto, Eva ^{[6
]}

Hasenauer, Jan ^{[3
,4
]}

机构：

[1] Ludwig Maximilians Univ Munchen, Fac Phys, D-80539 Munich, Germany

[2] Ludwig Maximilians Univ Munchen, Ctr NanoSci CeNS, D-80539 Munich, Germany

[3] Helmholtz Zentrum Munchen, Inst Computat Biol, D-85764 Munich, Germany

[4] Tech Univ Munich, Ctr Math, D-85748 Munich, Germany

[5] Univ Santiago de Compostela, Technol Inst Ind Math, Santiago De Compostela 15782, Spain

[6] IIM CSIC, Spanish Natl Res Council, Bio Proc Engn Grp, Vigo 36208, Spain

来源：

BIOINFORMATICS | 2018年 / 34卷 / 08期

关键词：

SYSTEMS;

D O I：

10.1093/bioinformatics/btx735

中图分类号：

Q5 [生物化学];

学科分类号：

071010 ; 081704 ;

摘要：

Motivation: Mathematical modeling using ordinary differential equations is used in systems biology to improve the understanding of dynamic biological processes. The parameters of ordinary differential equation models are usually estimated from experimental data. To analyze a priori the uniqueness of the solution of the estimation problem, structural identifiability analysis methods have been developed. Results: We introduce GenSSI 2.0, an advancement of the software toolbox GenSSI (Generating Series for testing Structural Identifiability). GenSSI 2.0 is the first toolbox for structural identifiability analysis to implement Systems Biology Markup Language import, state/parameter transformations and multi-experiment structural identifiability analysis. In addition, GenSSI 2.0 supports a range of MATLAB versions and is computationally more efficient than its previous version, enabling the analysis of more complex models.

引用

页码：1421 / 1423

页数：3

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