暂无分享,去创建一个
Eva Balsa-Canto | David Henriques | Julio Saez-Rodriguez | Julio R. Banga | Anton Crombach | Kieran Smallbone | Alejandro Fernández Villaverde | Joachim Schmid | Sophia Bongard | Damjan Cicin-Sain | Pedro Mendes | Klaus Mauch | Johannes Jaeger | J. Banga | P. Mendes | J. Schmid | K. Mauch | J. Sáez-Rodríguez | K. Smallbone | J. Jaeger | E. Balsa-Canto | A. F. Villaverde | David Henriques | Anton Crombach | S. Bongard | Damjan Cicin-Sain | Kieran Smallbone | Johannes Jaeger
[1] Pedro Mendes,et al. Yeast 5 – an expanded reconstruction of the Saccharomyces cerevisiae metabolic network , 2012, BMC Systems Biology.
[2] Steffen Klamt,et al. Transforming Boolean models to continuous models: methodology and application to T-cell receptor signaling , 2009, BMC Systems Biology.
[3] Anton Crombach,et al. Efficient Reverse-Engineering of a Developmental Gene Regulatory Network , 2012, PLoS Comput. Biol..
[4] Rudiyanto Gunawan,et al. Iterative approach to model identification of biological networks , 2005, BMC Bioinformatics.
[5] Eva Balsa-Canto,et al. Bioinformatics Applications Note Systems Biology Genssi: a Software Toolbox for Structural Identifiability Analysis of Biological Models , 2022 .
[6] Dag Wedelin,et al. Benchmarks for identification of ordinary differential equations from time series data , 2009, Bioinform..
[7] Carmen G. Moles,et al. Parameter estimation in biochemical pathways: a comparison of global optimization methods. , 2003, Genome research.
[8] Eva Balsa-Canto,et al. An iterative identification procedure for dynamic modeling of biochemical networks , 2010, BMC Systems Biology.
[9] Johannes Jaeger,et al. Gene Circuit Analysis of the Terminal Gap Gene huckebein , 2009, PLoS Comput. Biol..
[10] Julio Saez-Rodriguez,et al. Network topology and parameter estimation: from experimental design methods to gene regulatory network kinetics using a community based approach , 2014, BMC Systems Biology.
[11] Marija Cvijovic,et al. Kinetic models in industrial biotechnology - Improving cell factory performance. , 2014, Metabolic engineering.
[12] Dario Floreano,et al. Generating Realistic In Silico Gene Networks for Performance Assessment of Reverse Engineering Methods , 2009, J. Comput. Biol..
[13] Hong Wang,et al. Insights into the behaviour of systems biology models from dynamic sensitivity and identifiability analysis: a case study of an NF-kappaB signalling pathway. , 2006, Molecular bioSystems.
[14] Eva Balsa-Canto,et al. Parameter estimation and optimal experimental design. , 2008, Essays in biochemistry.
[15] C. Chassagnole,et al. Dynamic modeling of the central carbon metabolism of Escherichia coli. , 2002, Biotechnology and bioengineering.
[16] Gunnar Cedersund,et al. Conclusions via unique predictions obtained despite unidentifiability – new definitions and a general method , 2012, The FEBS journal.
[17] F. Wurm. Production of recombinant protein therapeutics in cultivated mammalian cells , 2004, Nature Biotechnology.
[18] David H. Sharp,et al. A connectionist model of development. , 1991, Journal of theoretical biology.
[19] Julio R. Banga,et al. Optimization in computational systems biology , 2008, BMC Systems Biology.
[20] Hugh D. Spence,et al. Minimum information requested in the annotation of biochemical models (MIRIAM) , 2005, Nature Biotechnology.
[21] Julio R. Banga,et al. A cooperative strategy for parameter estimation in large scale systems biology models , 2012, BMC Systems Biology.
[22] Steffen Klamt,et al. SBML qualitative models: a model representation format and infrastructure to foster interactions between qualitative modelling formalisms and tools , 2013, BMC Systems Biology.
[23] Rudiyanto Gunawan,et al. Parameter identifiability of power-law biochemical system models. , 2010, Journal of biotechnology.
[24] U. Sauer,et al. Advancing metabolic models with kinetic information. , 2014, Current opinion in biotechnology.
[25] Judith B. Zaugg,et al. Bacterial adaptation through distributed sensing of metabolic fluxes , 2010, Molecular systems biology.
[26] Mudita Singhal,et al. COPASI - a COmplex PAthway SImulator , 2006, Bioinform..
[27] Natal A. W. van Riel,et al. Dynamic modelling and analysis of biochemical networks: mechanism-based models and model-based experiments , 2006, Briefings Bioinform..
[28] Melanie I. Stefan,et al. BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models , 2010, BMC Systems Biology.
[29] Julio R. Banga,et al. Novel metaheuristic for parameter estimation in nonlinear dynamic biological systems , 2006, BMC Bioinformatics.
[30] Todd Munson,et al. Benchmarking optimization software with COPS 3.0. , 2001 .
[31] Dario Floreano,et al. GeneNetWeaver: in silico benchmark generation and performance profiling of network inference methods , 2011, Bioinform..
[32] Joseph J. DiStefano,et al. Dynamic Systems Biology Modeling and Simulation , 2015 .
[33] Xiaohua Xia,et al. On Identifiability of Nonlinear ODE Models and Applications in Viral Dynamics , 2011, SIAM Rev..
[34] Julio R. Banga,et al. Inference of complex biological networks: distinguishability issues and optimization-based solutions , 2011, BMC Systems Biology.
[35] Julio R. Banga,et al. An evolutionary method for complex-process optimization , 2010, Comput. Oper. Res..
[36] N. V. van Riel. Dynamic modelling and analysis of biochemical networks: mechanism-based models and model-based experiments. , 2006, Briefings in bioinformatics.
[37] D. Ramkrishna,et al. Modeling metabolic systems: the need for dynamics , 2013 .
[38] E D Sontag. For Differential Equations with r Parameters, 2r+1 Experiments Are Enough for Identification , 2003, J. Nonlinear Sci..
[39] Maksat Ashyraliyev,et al. Systems biology: parameter estimation for biochemical models , 2009, The FEBS journal.
[40] Neil Swainston,et al. Sustainable model building the role of standards and biological semantics. , 2011, Methods in enzymology.
[41] David H. Sharp,et al. Mechanism of eve stripe formation , 1995, Mechanisms of Development.
[42] N. Monk,et al. Bioattractors: dynamical systems theory and the evolution of regulatory processes , 2014, The Journal of physiology.
[43] J. Banga,et al. Structural Identifiability of Systems Biology Models: A Critical Comparison of Methods , 2011, PloS one.
[44] P. Mendes,et al. Large-Scale Metabolic Models: From Reconstruction to Differential Equations , 2013 .
[45] Nikolaus Hansen,et al. Benchmarking of Continuous Black Box Optimization Algorithms , 2012, Evolutionary Computation.
[46] Evangelos Simeonidis,et al. Flux balance analysis: a geometric perspective. , 2009, Journal of theoretical biology.
[47] F. Doyle,et al. A benchmark for methods in reverse engineering and model discrimination: problem formulation and solutions. , 2004, Genome research.
[48] Hiroaki Kitano,et al. The systems biology markup language (SBML): a medium for representation and exchange of biochemical network models , 2003, Bioinform..
[49] Michael R. Brent,et al. Benchmarking regulatory network reconstruction with GRENDEL , 2009, Bioinform..
[50] Reinhard Laubenbacher,et al. Comparison of Reverse‐Engineering Methods Using an in Silico Network , 2007, Annals of the New York Academy of Sciences.
[51] Daniel E. Zak,et al. Importance of input perturbations and stochastic gene expression in the reverse engineering of genetic regulatory networks: insights from an identifiability analysis of an in silico network. , 2003, Genome research.
[52] Rudiyanto Gunawan,et al. Incremental parameter estimation of kinetic metabolic network models , 2012, BMC Systems Biology.
[53] Michel Dumontier,et al. Controlled vocabularies and semantics in systems biology , 2011, Molecular systems biology.
[54] Edda Klipp,et al. Modular rate laws for enzymatic reactions: thermodynamics, elasticities and implementation , 2010, Bioinform..
[55] Gaudenz Danuser,et al. Linking data to models: data regression , 2006, Nature Reviews Molecular Cell Biology.
[56] Eva Balsa-Canto,et al. AMIGO, a toolbox for advanced model identification in systems biology using global optimization , 2011, Bioinform..
[57] David Henriques,et al. MEIGO: an open-source software suite based on metaheuristics for global optimization in systems biology and bioinformatics , 2013, BMC Bioinformatics.
[58] Julio R. Banga,et al. Reverse engineering and identification in systems biology: strategies, perspectives and challenges , 2014, Journal of The Royal Society Interface.
[59] H. D. Jong,et al. On the identifiability of metabolic network models , 2013, Journal of mathematical biology.
[60] H. Lodish. Molecular Cell Biology , 1986 .
[61] David H. Sharp,et al. Dynamic control of positional information in the early Drosophila embryo , 2004, Nature.
[62] Beatriz Peñalver Bernabé,et al. State–time spectrum of signal transduction logic models , 2012, Physical biology.
[63] Eva Balsa-Canto,et al. High-Confidence Predictions in Systems Biology Dynamic Models , 2014, PACBB.
[64] G. Cedersund,et al. Conservation laws and unidentifiability of rate expressions in biochemical models. , 2007, IET systems biology.
[65] Jorge J. Moré,et al. Digital Object Identifier (DOI) 10.1007/s101070100263 , 2001 .
[66] Eric Walter,et al. Identification of Parametric Models: from Experimental Data , 1997 .
[67] Pedro Mendes,et al. Artificial gene networks for objective comparison of analysis algorithms , 2003, ECCB.
[68] N A W van Riel,et al. Parameter uncertainty in biochemical models described by ordinary differential equations. , 2013, Mathematical biosciences.
[69] Eva Balsa-Canto,et al. Reverse-Engineering Post-Transcriptional Regulation of Gap Genes in Drosophila melanogaster , 2013, PLoS Comput. Biol..