A framework for parameter estimation and model selection from experimental data in systems biology using approximate Bayesian computation

Liepe, Juliane; Kirk, Paul; Filippi, Sarah; Toni, Tina; Barnes, C.; Stumpf, Michael

doi:10.1038/nprot.2014.025

Cited by 226 publications

(238 citation statements)

References 68 publications

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“…Model selection in systems biology can be performed using Bayesian inference (56). Here we perform parameter inference for model selection using approximate Bayesian computation, which forgoes evaluation of the likelihood function and instead calculates the (here Euclidean) distance between model and data (57), implemented in the ABC SysBio package (58). For each model we compare the total free β-catenin level (in some cases addition of two species) with the data provided by ref.…”

Section: Methodsmentioning

confidence: 99%

Parameter-free methods distinguish Wnt pathway models and guide design of experiments

MacLean

Rosen

Byrne

et al. 2015

Proc. Natl. Acad. Sci. U.S.A.

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The canonical Wnt signaling pathway, mediated by β-catenin, is crucially involved in development, adult stem cell tissue maintenance, and a host of diseases including cancer. We analyze existing mathematical models of Wnt and compare them to a new Wnt signaling model that targets spatial localization; our aim is to distinguish between the models and distill biological insight from them. Using Bayesian methods we infer parameters for each model from mammalian Wnt signaling data and find that all models can fit this time course. We appeal to algebraic methods (concepts from chemical reaction network theory and matroid theory) to analyze the models without recourse to specific parameter values. These approaches provide insight into aspects of Wnt regulation: the new model, via control of shuttling and degradation parameters, permits multiple stable steady states corresponding to stem-like vs. committed cell states in the differentiation hierarchy. Our analysis also identifies groups of variables that should be measured to fully characterize and discriminate between competing models, and thus serves as a guide for performing minimal experiments for model comparison. T he Wnt signaling pathway plays a key role in essential cellular processes ranging from proliferation and cell specification during development to adult stem cell maintenance and wound repair (1). Dysfunction of Wnt signaling is implicated in many pathological conditions, including degenerative diseases and cancer (2-4). Despite many molecular advances, the pathway dynamics are still not well understood. Theoretical investigations of the Wnt/β-catenin pathway serve as testbeds for working hypotheses (5-12).We focus on models of canonical Wnt pathway processes with the aim of elucidating mechanisms, predicting function, and identifying key pathway components in adult tissues, such as colonic crypts. We compare four preexisting ordinary differential equation models (5-8) and find, using injectivity theory, that for any given conditions and parameter values, none of the models is capable of multiple cellular responses.In many tissues Wnt plays a crucial role in cell fate specification (3). At the base of colonic crypts, cells exist in a stem-like, proliferative phenotype in the presence of Wnt. As these cells' progeny move up the crypt axis they enter a Wnt-low environment and change fate (perhaps reversibly), becoming differentiated, specialized gut cells (13). In neuronal and endocrinal tissues, Wnt/β-catenin data suggest cell fate plasticity under different environmental conditions (14, 15). Here, we introduce a new model motivated by experimental findings not described in previous models (16-18) to investigate bistable switching in the Wnt pathway. We find the new model to be capable of multiple cellular responses; furthermore, our parameter-free techniques identify that molecular shuttling (between cytoplasm and nucleus) and degradation together may serve as a possible mechanism for governing bistability in the pathway, corresponding to, for example, ...

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Section: Methodsmentioning

confidence: 99%

Parameter-free methods distinguish Wnt pathway models and guide design of experiments

MacLean

Rosen

Byrne

et al. 2015

Proc. Natl. Acad. Sci. U.S.A.

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“…On the other hand, it also enables to explore the system function at various levels and help to generate hypothesis about biological experiments. However, there are some limitations of this method, like identification of unknown parameters which are estimated from experimental results (Liepe et al, 2014;Denget al, 2014;Raue et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

Parameters Involved in Autophosphorylation in Chronic Myeloid Leukemia: a Systems Biology Approach

Kumar

Tichkule²,

Raj³

et al. 2015

Asian Pacific Journal of Cancer Prevention

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“…Approximate Bayesian Computation (ABC) methods have emerged over the past few years to overcome this limitation [31]. These methods approximate the likelihood function by simulations, the outcomes of which are compared with the observed data [32].…”

Section: 5sequential Monte Carlo For Approximate Bayesian Computationmentioning

confidence: 99%

“…These methods approximate the likelihood function by simulations, the outcomes of which are compared with the observed data [32]. The Sequential Monte Carlo (SMC) algorithm is amongst the most efficient samplers to perform ABC [31,33]. Briefly, a set of parameter sets (particles) is…”

Section: 5sequential Monte Carlo For Approximate Bayesian Computationmentioning

confidence: 99%

A probabilistic framework for the exploration of enzymatic capabilities based on feasible kinetics and control analysis

Saa

Nielsen

2016

Biochimica et Biophysica Acta (BBA) - General Subjects

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BackgroundAnalysis of limiting steps within enzyme-catalyzed reactions is fundamental to understand their behavior and regulation. Methods capable of unravelling control properties and exploring kinetic capabilities of enzymatic reactions would be particularly useful for protein and metabolic engineering. While single-enzyme control analysis formalism has previously been applied to well-studied enzymatic mechanisms, broader application of formalism is limited in practice by the limited amount of kinetic data and the difficulty of describing complex allosteric mechanisms. MethodsTo overcome these limitations, we present here a probabilistic framework enabling control analysis of previously unexplored mechanisms under uncertainty. By combining a thermodynamically consistent parameterization with an efficient Sequential Monte Carlosampler embedded in a Bayesian setting, this framework yields insights into the capabilities of enzyme-catalyzed reactions with modest kinetic information, provided that the catalytic mechanism and a thermodynamic reference point are defined. ResultsThe framework was used to unravel the impact of thermodynamic affinity, substrate saturation levels and effector concentrations on the flux control and response coefficients of a diverse set of enzymatic reactions. ConclusionsOur results highlight the importance of the metabolic context in the control analysis of isolated enzymes as well as the use of statistically sound methods for their interpretation. General SignificanceThis framework significantly expands our current capabilities for unravelling the control properties of general reaction kinetics with limited amount of information. This framework will be useful for both theoreticians and experimentalists in the field.

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A framework for parameter estimation and model selection from experimental data in systems biology using approximate Bayesian computation

Cited by 226 publications

References 68 publications

Parameter-free methods distinguish Wnt pathway models and guide design of experiments

Parameter-free methods distinguish Wnt pathway models and guide design of experiments

Parameters Involved in Autophosphorylation in Chronic Myeloid Leukemia: a Systems Biology Approach

A probabilistic framework for the exploration of enzymatic capabilities based on feasible kinetics and control analysis

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