scholarly journals Modular assembly of dynamic models in systems biology

2021 ◽  
Vol 17 (10) ◽  
pp. e1009513
Author(s):  
Michael Pan ◽  
Peter J. Gawthrop ◽  
Joseph Cursons ◽  
Edmund J. Crampin
Keyword(s):  
Systems Biology ◽  
Large Scale ◽  
Dynamic Models ◽  
Mitogen Activated Protein Kinase ◽  
Bond Graphs ◽  
Modular Assembly ◽  
Scale Models ◽  
Mitogen Activated Protein ◽  
Recent Developments ◽  
Modular Modelling

It is widely acknowledged that the construction of large-scale dynamic models in systems biology requires complex modelling problems to be broken up into more manageable pieces. To this end, both modelling and software frameworks are required to enable modular modelling. While there has been consistent progress in the development of software tools to enhance model reusability, there has been a relative lack of consideration for how underlying biophysical principles can be applied to this space. Bond graphs combine the aspects of both modularity and physics-based modelling. In this paper, we argue that bond graphs are compatible with recent developments in modularity and abstraction in systems biology, and are thus a desirable framework for constructing large-scale models. We use two examples to illustrate the utility of bond graphs in this context: a model of a mitogen-activated protein kinase (MAPK) cascade to illustrate the reusability of modules and a model of glycolysis to illustrate the ability to modify the model granularity.

scholarly journals Modular assembly of dynamic models in systems biology

2021 ◽  
Author(s):  
Michael Pan ◽  
Peter J. Gawthrop ◽  
Joseph Cursons ◽  
Edmund Crampin
Keyword(s):  
Systems Biology ◽  
Large Scale ◽  
Dynamic Models ◽  
Mitogen Activated Protein Kinase ◽  
Bond Graphs ◽  
Modular Assembly ◽  
Scale Models ◽  
Mitogen Activated Protein ◽  
Recent Developments ◽  
Modular Modelling

It is widely acknowledged that the construction of large-scale dynamic models in systems biology requires complex modelling problems to be broken up into more manageable pieces. To this end, both modelling and software frameworks are required to enable modular modelling. While there has been consistent progress in the development of software tools to enhance model reusability, there has been a relative lack of consideration for how underlying biophysical principles can be applied to this space. Bond graphs combine the aspects of both modularity and physics-based modelling. In this paper, we argue that bond graphs are compatible with recent developments in modularity and abstraction in systems biology, and are thus a desirable framework for constructing large-scale models. We use two examples to illustrate the utility of bond graphs in this context: a model of a mitogen-activated protein kinase (MAPK) cascade to illustrate the reusability of modules and a model of glycolysis to illustrate the ability to modify the model granularity.

A systems- and signal-oriented approach to intracellular dynamics

2005 ◽  
Vol 33 (3) ◽  
pp. 507-515 ◽  
Author(s):  
O. Wolkenhauer ◽  
S.N. Sreenath ◽  
P. Wellstead ◽  
M. Ullah ◽  
K.-H. Cho
Keyword(s):  
Systems Biology ◽  
Dynamic Models ◽  
Cell Signalling ◽  
Science Research ◽  
Predictive Modelling ◽  
Mitogen Activated Protein Kinase ◽  
Simulation Studies ◽  
Simulated Environment ◽  
Mitogen Activated Protein ◽  
Modelling Simulation

A mathematical understanding of regulation, and, in particular, the role of feedback, has been central to the advance of the physical sciences and technology. In this article, the framework provided by systems biology is used to argue that the same can be true for molecular biology. In particular, and using basic modular methods of mathematical modelling which are standard in control theory, a set of dynamic models is developed for some illustrative cell signalling processes. These models, supported by recent experimental evidence, are used to argue that a control theoretical approach to the mechanisms of feedback in intracellular signalling is central to furthering our understanding of molecular communication. As a specific example, a MAPK (mitogen-activated protein kinase) signalling pathway is used to show how potential feedback mechanisms in the signalling process can be investigated in a simulated environment. Such ‘what if’ modelling/simulation studies have been an integral part of physical science research for many years. Using tools of control systems analysis, as embodied in the disciplines of systems biology, similar predictive modelling/simulation studies are now bearing fruit in cell signalling research.

scholarly journals An ultrasensitive fiveplex activity assay for cellular kinases

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Christian M. Smolko ◽  
Kevin A. Janes
Keyword(s):  
Protein Kinase ◽  
Protein Interactions ◽  
Posttranslational Modifications ◽  
Large Scale ◽  
Cell Types ◽  
Mitogen Activated Protein Kinase ◽  
Activity Measurement ◽  
Kinase Substrate ◽  
Iκb Kinase ◽  
Mitogen Activated Protein

AbstractProtein kinases are enzymes whose abundance, protein-protein interactions, and posttranslational modifications together determine net signaling activity in cells. Large-scale data on cellular kinase activity are limited, because existing assays are cumbersome, poorly sensitive, low throughput, and restricted to measuring one kinase at a time. Here, we surmount the conventional hurdles of activity measurement with a multiplexing approach that leverages the selectivity of individual kinase-substrate pairs. We demonstrate proof of concept by designing an assay that jointly measures activity of five pleiotropic signaling kinases: Akt, IκB kinase (IKK), c-jun N-terminal kinase (JNK), mitogen-activated protein kinase (MAPK)-extracellular regulated kinase kinase (MEK), and MAPK-activated protein kinase-2 (MK2). The assay operates in a 96-well format and specifically measures endogenous kinase activation with coefficients of variation less than 20%. Multiplex tracking of kinase-substrate pairs reduces input requirements by 25-fold, with ~75 µg of cellular extract sufficient for fiveplex activity profiling. We applied the assay to monitor kinase signaling during coxsackievirus B3 infection of two different host-cell types and identified multiple differences in pathway dynamics and coordination that warrant future study. Because the Akt–IKK–JNK–MEK–MK2 pathways regulate many important cellular functions, the fiveplex assay should find applications in inflammation, environmental-stress, and cancer research.

scholarly journals A semantics, energy-based approach to automate biomodel composition

2021 ◽  
Author(s):  
Niloofar Shahidi ◽  
Michael Pan ◽  
Kenneth Tran ◽  
Edmund Crampin ◽  
David Phillip Nickerson
Keyword(s):  
Large Scale ◽  
Biological Systems ◽  
Mapk Cascade ◽  
Bond Graphs ◽  
Hierarchical Modelling ◽  
Semantic Annotations ◽  
Comprehensive Knowledge ◽  
Scale Models ◽  
Systems Models ◽  
Common Components

Hierarchical modelling is essential to achieving complex, large-scale models. However, not all modelling schemes support hierarchical composition, and correctly mapping points of connection between models requires comprehensive knowledge of each model's components and assumptions. To address these challenges in integrating biosimulation models, we propose an approach to automatically and confidently compose biosimulation models. The approach uses bond graphs to combine aspects of physical and thermodynamics-based modelling with biological semantics. We improved on existing approaches by using semantic annotations to automate the recognition of common components. The approach is illustrated by coupling a model of the Ras-MAPK cascade to a model of the upstream activation of EGFR. Through this methodology, we aim to assist researchers and modellers in readily having access to more comprehensive biological systems models.

scholarly journals Integrated Molecular Characterisation of the MAPK Pathways in Human Cancers

2020 ◽  
Author(s):  
Musalula Sinkala ◽  
Panji Nkhoma ◽  
Nicola Mulder ◽  
Darren Patrick Martin
Keyword(s):  
Cancer Cells ◽  
Large Scale ◽  
Mapk Pathway ◽  
Gene Knockout ◽  
Mitogen Activated Protein Kinase ◽  
Mapk Signalling Pathway ◽  
Mapk Pathways ◽  
Human Cancers ◽  
Mitogen Activated Protein ◽  
Molecular Aberrations

AbstractThe mitogen-activated protein kinase (MAPK) pathways are a crucial regulator of the cellular processes that fuel the malignant transformation of normal cells. The genetic underpinnings of molecular aberrations which lead to cancer involve mutations in and, transcription variations of, various MAPK pathway genes. Here, we use datasets of 40,848 patient-derived tumours representing 101 distinct human cancers to identify cancer-associated mutations in MAPK signalling pathway genes. We identify the subset of these genes within which mutations tend to be associated with the worst disease outcomes. Furthermore, by integrating information extracted from various large-scale molecular datasets, we expose the relationship between the fitness of cancer cells after CRISPR mediated gene knockout of MAPK pathway genes, and their dose-responses to MAPK pathway inhibitors. Besides providing new insights into MAPK pathways, we unearth vulnerabilities in specific pathway genes that are reflected in the responses of cancer cells to MAPK drug perturbations: a revelation with great potential for guiding the development of innovative therapeutic strategies.

Complexity and Modularity of MAPK Signaling Networks

2013 ◽  
pp. 676-689
Author(s):  
George V. Popescu ◽  
Sorina C. Popescu
Keyword(s):  
Large Scale ◽  
Mapk Signaling ◽  
Mitogen Activated Protein Kinase ◽  
Signaling Networks ◽  
Mapk Cascades ◽  
Mitogen Activated Protein ◽  
Computational Modeling And Simulation ◽  
Definition Of

Signaling through mitogen-activated protein kinase (MAPK) cascades is a conserved and fundamental process in all eukaryotes. This chapter reviews recent progress made in the identification of components of MAPK signaling networks using novel large scale experimental methods. It also presents recent landmarks in the computational modeling and simulation of the dynamics of MAPK signaling modules. The in vitro MAPK signaling network reconstructed from predicted phosphorylation events is dense, supporting the hypothesis of a combinatorial control of transcription through selective phosphorylation of sets of transcription factors. Despite the fact that additional co-factors and scaffold proteins may regulate the dynamics of signal transduction in vivo, the complexity of MAPK signaling networks supports a new model that departs significantly from that of the classical definition of a MAPK cascade.

scholarly journals Efficient parameterization of large-scale dynamic models based on relative measurements

2019 ◽  
Author(s):  
Leonard Schmiester ◽  
Yannik Schälte ◽  
Fabian Fröhlich ◽  
Jan Hasenauer ◽  
Daniel Weindl
Keyword(s):  
Large Scale ◽  
Dynamic Models ◽  
Error Model ◽  
Supplementary Information ◽  
Reaction Networks ◽  
Model Parameters ◽  
Biological Processes ◽  
Wide Range ◽  
Scale Models ◽  
Relative Measurements

Abstract Motivation Mechanistic models of biochemical reaction networks facilitate the quantitative understanding of biological processes and the integration of heterogeneous datasets. However, some biological processes require the consideration of comprehensive reaction networks and therefore large-scale models. Parameter estimation for such models poses great challenges, in particular when the data are on a relative scale. Results Here, we propose a novel hierarchical approach combining (i) the efficient analytic evaluation of optimal scaling, offset and error model parameters with (ii) the scalable evaluation of objective function gradients using adjoint sensitivity analysis. We evaluate the properties of the methods by parameterizing a pan-cancer ordinary differential equation model (>1000 state variables, >4000 parameters) using relative protein, phosphoprotein and viability measurements. The hierarchical formulation improves optimizer performance considerably. Furthermore, we show that this approach allows estimating error model parameters with negligible computational overhead when no experimental estimates are available, providing an unbiased way to weight heterogeneous data. Overall, our hierarchical formulation is applicable to a wide range of models, and allows for the efficient parameterization of large-scale models based on heterogeneous relative measurements. Availability and implementation Supplementary code and data are available online at http://doi.org/10.5281/zenodo.3254429 and http://doi.org/10.5281/zenodo.3254441. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals An ultrasensitive fiveplex activity assay for cellular kinases

2019 ◽  
Author(s):  
Christian M. Smolko ◽  
Kevin A. Janes
Keyword(s):  
Protein Kinase ◽  
Protein Interactions ◽  
Posttranslational Modifications ◽  
Large Scale ◽  
Cell Types ◽  
Mitogen Activated Protein Kinase ◽  
Activity Measurement ◽  
Kinase Substrate ◽  
Iκb Kinase ◽  
Mitogen Activated Protein

ABSTRACTProtein kinases are enzymes whose abundance, protein-protein interactions, and posttranslational modifications together determine net signaling activity in cells. Large-scale data on cellular kinase activity are limited, because existing assays are cumbersome, poorly sensitive, low throughput, and restricted to measuring one kinase at a time. Here, we surmount the conventional hurdles of activity measurement with a multiplexing approach that leverages the selectivity of individual kinase-substrate pairs. We demonstrate proof of concept by designing an assay that jointly measures activity of five pleiotropic signaling kinases: Akt, IκB kinase (IKK), c-jun N-terminal kinase (JNK), mitogen-activated protein kinase (MAPK)-extracellular regulated kinase kinase (MEK), and MAPK-activated protein kinase-2 (MK2). The assay operates in a 96-well format and specifically measures endogenous kinase activation with coefficients of variation less than 20%. Multiplex tracking of kinase-substrate pairs reduces input requirements by 25-fold, with ~75 μg of cellular extract sufficient for fiveplex activity profiling. We applied the assay to monitor kinase signaling during coxsackievirus B3 infection of two different host-cell types and identified multiple differences in pathway dynamics and coordination that warrant future study. Because the Akt–IKK–JNK–MEK–MK2 pathways regulate many important cellular functions, the fiveplex assay should find applications in inflammation, environmental-stress, and cancer research.

scholarly journals Modelling and Forecasting Domestic Tourism. Case Study from Armenia

2021 ◽  
Vol 5 (2) ◽  
pp. 96-110
Author(s):  
Karen Poghosyan ◽  
Gayane Tovmasyan
Keyword(s):  
Large Scale ◽  
Dynamic Models ◽  
Dynamic Modelling ◽  
Tourism Development ◽  
Point Of View ◽  
Sufficient Evidence ◽  
Small Scale ◽  
Scale Models ◽  
Domestic Tourism ◽  
Modelling And Forecasting

This paper summarizes the arguments and counterarguments within the scientific discussion on the issue of modelling and forecasting domestic tourism. During Covid-19 many countries tried to develop domestic tourism as an alternative to inbound tourism. In Armenia domestic tourism has grown recently, and in 2020 the decrease was 33% compared to last year. The main purpose of the research is to model and forecast domestic tourism growth in Armenia. Systematization of the literary sources and approaches for solving the problem indicates that many models and different variables are used to forecast tourism development. Methodological tools of the research methods were static and dynamic models, years of research were 2001-2020, quarterly data. The paper presents the results of an empirical analysis, which showed that with the static regression analysis a 1% change in GDP will lead to a change of 4.43% in the number of domestic tourists, a 1% change in the CPI will lead to a 14.55% change in the number of domestic tourists. For dynamic modelling we used 12 competing short-term forecasting models. Based on the recursive and rolling forecast simulation results we concluded that out-of-sample forecasts obtained by the small-scale models outperform forecasts obtained by the large-scale models at all forecast horizons. So, the forecasts of the domestic tourists’ growth obtained by small-scale models are more appropriate from the practical point of view. Then, in order to check whether the differences in forecasts obtained by the different models are statistically significant we applied Diebold-Mariano test. Based on the results of this test we concluded that there is not sufficient evidence to favor large-scale over small-scale models. This means that the forecast results obtained for domestic tourist growth by using the small scale models would not be statistically different from the results obtained by the large scale models. Based on the analysis, the forecasted values for domestic tourists for the future years were determined. The results of the research can be useful for state bodies, as well as private organizations, and for everybody who wants to model and forecast tourism development.

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