scholarly journals Dynamic compensation, parameter identifiability, and equivariances

2016 ◽  
Author(s):  
Eduardo Sontag
Keyword(s):  
Systems Biology ◽  
Mathematical Models ◽  
Glucose Homeostasis ◽  
Regulatory Mechanisms ◽  
Dynamic Compensation ◽  
Parameter Identifiability ◽  
Mathematical Notion ◽  
System Equivalence ◽  
Biological Circuits

AbstractA recent paper by Karin, Swisa, Glaser, Dor, and Alon introduced the mathematical notion of dynamical compensation (DC) in biological circuits, arguing that DC helps explain important features of glucose homeostasis as well as other key physiological regulatory mechanisms. The present paper establishes a connection between DC and two well-known notions in systems biology: system equivalence and parameter (un)identifiability. This recasting leads to effective tests for verifying DC in mathematical models.

scholarly journals Identification of Key Proteins Involved in Axon Guidance Related Disorders: A Systems Biology Approach

2018 ◽  
Author(s):  
Ishtiaque Ahammad
Keyword(s):  
Systems Biology ◽  
Axon Guidance ◽  
Molecular Mechanisms ◽  
Regulatory Mechanisms ◽  
Ppi Network ◽  
Retraction Syndrome ◽  
Horizontal Gaze ◽  
Duane Retraction Syndrome ◽  
Type 3 ◽  
Congenital Fibrosis

Axon guidance is a crucial process for growth of the central and peripheral nervous systems. In this study, 3 axon guidance related disorders, namely- Duane Retraction Syndrome (DRS) , Horizontal Gaze Palsy with Progressive Scoliosis (HGPPS) and Congenital fibrosis of the extraocular muscles type 3 (CFEOM3) were studied using various Systems Biology tools to identify the genes and proteins involved with them to get a better idea about the underlying molecular mechanisms including the regulatory mechanisms. Based on the analyses carried out, 7 significant modules have been identified from the PPI network. Five pathways/processes have been found to be significantly associated with DRS, HGPPS and CFEOM3 associated genes. From the PPI network, 3 have been identified as hub proteins- DRD2, UBC and CUL3.

scholarly journals Analysing and simulating energy-based models in biology using BondGraphTools

2021 ◽  
Author(s):  
Peter Cudmore ◽  
Michael Pan ◽  
Peter J. Gawthrop ◽  
Edmund J. Crampin
Keyword(s):  
Systems Biology ◽  
Mathematical Models ◽  
Bond Graph ◽  
Experimental Measurements ◽  
Bond Graphs ◽  
Graph Models ◽  
Conservation Of Energy ◽  
Conservation Of Mass ◽  
Physical Systems ◽  
Complex Interactions

AbstractLike all physical systems, biological systems are constrained by the laws of physics. However, mathematical models of biochemistry frequently neglect the conservation of energy, leading to unrealistic behaviour. Energy-based models that are consistent with conservation of mass, charge and energy have the potential to aid the understanding of complex interactions between biological components, and are becoming easier to develop with recent advances in experimental measurements and databases. In this paper, we motivate the use of bond graphs (a modelling tool from engineering) for energy-based modelling and introduce, BondGraphTools, a Python library for constructing and analysing bond graph models. We use examples from biochemistry to illustrate how BondGraphTools can be used to automate model construction in systems biology while maintaining consistency with the laws of physics.

The usefulness of post-genomics tools for characterization of the amine cross-talk in mammalian cells

2007 ◽  
Vol 35 (2) ◽  
pp. 381-385 ◽  
Author(s):  
F. Sánchez-Jiménez ◽  
R. Montañez ◽  
F. Correa-Fiz ◽  
P. Chaves ◽  
C. Rodríguez-Caso ◽  
...  
Keyword(s):  
Systems Biology ◽  
Mathematical Models ◽  
Mammalian Cells ◽  
State Of The Art ◽  
Molecular Approaches ◽  
Amine Metabolism ◽  
Genomics Tools ◽  
Stored Information

Evidence is growing in favour of a relationship between cancer and chronic inflammation, and particularly of the role of a polyamine and histamine metabolic interplay involved in these physiopathological problems, which are indeed highly complex biological systems. Decodification of the complex inter- and intra-cellular signalling mechanisms that control these effects is not an easy task, which must be helped by systems biology technologies, including new tools for location and integration of database-stored information and predictive mathematical models, as well as functional genomics and other experimental molecular approaches necessary for hypothesis validation. We review the state of the art and present our latest efforts in this area, focused on the amine metabolism field.

scholarly journals A hierarchical Bayesian framework for understanding the spatiotemporal dynamics of the intestinal epithelium

2016 ◽  
Author(s):  
O.J. Maclaren ◽  
A. Parker ◽  
C. Pin ◽  
S.R. Carding ◽  
A.J.M. Watson ◽  
...  
Keyword(s):  
Systems Biology ◽  
Mathematical Models ◽  
Intestinal Epithelium ◽  
Cellular Migration ◽  
Cell Labelling ◽  
Mechanistic Models ◽  
Hierarchical Approach ◽  
Multiple Sources ◽  
Cellular Models ◽  
Out Of Sample

AbstractOur work addresses two key challenges, one biological and one methodological. First, we aim to understand how proliferation and cellular migration rates in the intestinal epithelium are related under healthy, damaged (Ara-C treated) and recovering conditions, and how these relations can be used to identify mechanisms of repair and regeneration. We analyse new data, presented in more detail in a companion paper, in which BrdU/IdU cell-labelling experiments were performed under these respective conditions. Second, in considering how to more rigorously process these data and interpret them using mathematical models, we develop a probabilistic, hierarchical framework. This framework provides a best-practice approach for systematically modelling and understanding the uncertainties that can otherwise undermine drawing reliable conclusions - uncertainties in experimental measurement and treatment, difficult-to-compare mathematical models of underlying mechanisms, and unknown or unobserved parameters. Both discrete and continuous mechanistic models are considered and related via hierarchical conditional probability assumptions. This allows the incorporation of features of both continuum tissue models and discrete cellular models. We perform model checks on both in-sample and out-of-sample datasets and use these checks to illustrate how to test possible model improvements and assess the robustness of our conclusions. This allows us to consider - and ultimately decide against - the need to retain finite-cell-size effects to explain a small misfit appearing in one set of long-time, out-of-sample predictions. Our approach leads us to conclude, for the present set of experiments, that a primarily proliferation-driven model is adequate for predictions over most time-scales. We describe each stage of our framework in detail, and hope that the present work may also serve as a guide for other applications of the hierarchical approach to problems in computational and systems biology more generally.Author SummaryThe intestinal epithelium serves as an important model system for studying the dynamics and regulation of multicellular populations. It is characterised by rapid rates of self-renewal and repair; failure of the regulation of these processes is thought to explain, in part, why many tumours occur in the intestinal and similar epithelial tissues. These features have led to a large amount of work on estimating rate parameters in the intestine. There still remain, however, large gaps between the raw data collected, the experimental interpretation of these data, and speculative mechanistic models for underlying processes. In our view hierarchical statistical modelling provides an ideal, but currently underutilised, method to begin to bridge these gaps. This approach makes essential use of the distinction between ‘measurement’, ‘process’ and ‘parameter’ models, giving an explicit framework for combining experimental data and mechanistic modelling in the presence of multiple sources of uncertainty. As we illustrate, the hierarchical approach also provides a suitable framework for addressing other methodological questions of broader interest in systems biology: how to systematically relate discrete and continuous mechanistic models; how to formally interpret and visualise statistical evidence; and how to express causal assumptions in terms of conditional independence.

scholarly journals Identification of Key Proteins Involved in Axon Guidance Related Disorders: A Systems Biology Approach

2018 ◽  
Author(s):  
Ishtiaque Ahammad
Keyword(s):  
Systems Biology ◽  
Axon Guidance ◽  
Molecular Mechanisms ◽  
Regulatory Mechanisms ◽  
Ppi Network ◽  
Retraction Syndrome ◽  
Horizontal Gaze ◽  
Duane Retraction Syndrome ◽  
Type 3 ◽  
Congenital Fibrosis

<p>Axon guidance is a crucial process for growth of the central and peripheral nervous systems. In this study, 3 axon guidance related disorders, namely- Duane Retraction Syndrome (DRS) , Horizontal Gaze Palsy with Progressive Scoliosis (HGPPS) and Congenital fibrosis of the extraocular muscles type 3 (CFEOM3) were studied using various Systems Biology tools to identify the genes and proteins involved with them to get a better idea about the underlying molecular mechanisms including the regulatory mechanisms. Based on the analyses carried out, 7 significant modules have been identified from the PPI network. Five pathways/processes have been found to be significantly associated with DRS, HGPPS and CFEOM3 associated genes. From the PPI network, 3 have been identified as hub proteins- DRD2, UBC and CUL3. </p>

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