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BMC Systems Biology

Michael A Rowland, Hannah Wear, Karen H Watanabe, Kurt A Gust, Michael L Mayo
BACKGROUND: A challenge of in vitro to in vivo extrapolation (IVIVE) is to predict the physical state of organisms exposed to chemicals in the environment from in vitro exposure assay data. Although toxicokinetic modeling approaches promise to bridge in vitro screening data with in vivo effects, they are often encumbered by a need for redesign or re-parameterization when applied to different tissues or chemicals. RESULTS: We demonstrate a parameterization of reverse toxicokinetic (rTK) models developed for the adult zebrafish (Danio rerio) based upon particle swarm optimizations (PSO) of the chemical uptake and degradation rates that predict bioconcentration factors (BCF) for a broad range of chemicals...
August 7, 2018: BMC Systems Biology
Minoo Ashtiani, Ali Salehzadeh-Yazdi, Zahra Razaghi-Moghadam, Holger Hennig, Olaf Wolkenhauer, Mehdi Mirzaie, Mohieddin Jafari
BACKGROUND: Numerous centrality measures have been introduced to identify "central" nodes in large networks. The availability of a wide range of measures for ranking influential nodes leaves the user to decide which measure may best suit the analysis of a given network. The choice of a suitable measure is furthermore complicated by the impact of the network topology on ranking influential nodes by centrality measures. To approach this problem systematically, we examined the centrality profile of nodes of yeast protein-protein interaction networks (PPINs) in order to detect which centrality measure is succeeding in predicting influential proteins...
July 31, 2018: BMC Systems Biology
Håvard G Frøysa, Shirin Fallahi, Nello Blaser
BACKGROUND: The dynamics of biochemical networks can be modelled by systems of ordinary differential equations. However, these networks are typically large and contain many parameters. Therefore model reduction procedures, such as lumping, sensitivity analysis and time-scale separation, are used to simplify models. Although there are many different model reduction procedures, the evaluation of reduced models is difficult and depends on the parameter values of the full model. There is a lack of a criteria for evaluating reduced models when the model parameters are uncertain...
July 27, 2018: BMC Systems Biology
Rajat Anand, Dipanka Tanu Sarmah, Samrat Chatterjee
BACKGROUND: Metabolic disorders such as obesity and diabetes are diseases which develop gradually over time in an individual and through the perturbations of genes. Systematic experiments tracking disease progression at gene level are usually conducted giving a temporal microarray data. There is a need for developing methods to analyze such complex data and extract important proteins which could be involved in temporal progression of the data and hence progression of the disease. RESULTS: In the present study, we have considered a temporal microarray data from an experiment conducted to study development of obesity and diabetes in mice...
July 25, 2018: BMC Systems Biology
Hooman Sedghamiz, Matthew Morris, Travis J A Craddock, Darrell Whitley, Gordon Broderick
BACKGROUND: The hypothalamic-pituitary-adrenal (HPA) axis is a central regulator of stress response and its dysfunction has been associated with a broad range of complex illnesses including Gulf War Illness (GWI) and Chronic Fatigue Syndrome (CFS). Though classical mathematical approaches have been used to model HPA function in isolation, its broad regulatory interactions with immune and central nervous function are such that the biological fidelity of simulations is undermined by the limited availability of reliable parameter estimates...
July 17, 2018: BMC Systems Biology
Guan-Sheng Liu, Richard Ballweg, Alan Ashbaugh, Yin Zhang, Joseph Facciolo, Melanie T Cushion, Tongli Zhang
BACKGROUND: The yeast-like fungi Pneumocystis, resides in lung alveoli and can cause a lethal infection known as Pneumocystis pneumonia (PCP) in hosts with impaired immune systems. Current therapies for PCP, such as trimethoprim-sulfamethoxazole (TMP-SMX), suffer from significant treatment failures and a multitude of serious side effects. Novel therapeutic approaches (i.e. newly developed drugs or novel combinations of available drugs) are needed to treat this potentially lethal opportunistic infection...
July 17, 2018: BMC Systems Biology
Bob Strome, Ian Shenyen Hsu, Mitchell Li Cheong Man, Taraneh Zarin, Alex Nguyen Ba, Alan M Moses
BACKGROUND: The effort to characterize intrinsically disordered regions of signaling proteins is rapidly expanding. An important class of disordered interaction modules are ubiquitous and functionally diverse elements known as short linear motifs (SLiMs). RESULTS: To further examine the role of SLiMs in signal transduction, we used a previously devised bioinformatics method to predict evolutionarily conserved SLiMs within a well-characterized pathway in S. cerevisiae...
July 3, 2018: BMC Systems Biology
Bin Huang, Dongya Jia, Jingchen Feng, Herbert Levine, José N Onuchic, Mingyang Lu
BACKGROUND: One of the major challenges in traditional mathematical modeling of gene regulatory circuits is the insufficient knowledge of kinetic parameters. These parameters are often inferred from existing experimental data and/or educated guesses, which can be time-consuming and error-prone, especially for large networks. RESULTS: We present a user-friendly computational tool for the community to use our newly developed method named random circuit perturbation (RACIPE), to explore the robust dynamical features of gene regulatory circuits without the requirement of detailed kinetic parameters...
June 19, 2018: BMC Systems Biology
Robert W Smith, Rik P van Rosmalen, Vitor A P Martins Dos Santos, Christian Fleck
BACKGROUND: Models of metabolism are often used in biotechnology and pharmaceutical research to identify drug targets or increase the direct production of valuable compounds. Due to the complexity of large metabolic systems, a number of conclusions have been drawn using mathematical methods with simplifying assumptions. For example, constraint-based models describe changes of internal concentrations that occur much quicker than alterations in cell physiology. Thus, metabolite concentrations and reaction fluxes are fixed to constant values...
June 19, 2018: BMC Systems Biology
Peter D Karp, Daniel Weaver, Mario Latendresse
BACKGROUND: Reaction gap filling is a computational technique for proposing the addition of reactions to genome-scale metabolic models to permit those models to run correctly. Gap filling completes what are otherwise incomplete models that lack fully connected metabolic networks. The models are incomplete because they are derived from annotated genomes in which not all enzymes have been identified. Here we compare the results of applying an automated likelihood-based gap filler within the Pathway Tools software with the results of manually gap filling the same metabolic model...
June 19, 2018: BMC Systems Biology
Abel Folch-Fortuny, Bas Teusink, Huub C J Hoefsloot, Age K Smilde, Alberto Ferrer
BACKGROUND: A novel framework is proposed to analyse metabolic fluxes in non-steady state conditions, based on the new concept of dynamic elementary mode (dynEM): an elementary mode activated partially depending on the time point of the experiment. RESULTS: Two methods are introduced here: dynamic elementary mode analysis (dynEMA) and dynamic elementary mode regression discriminant analysis (dynEMR-DA). The former is an extension of the recently proposed principal elementary mode analysis (PEMA) method from steady state to non-steady state scenarios...
June 18, 2018: BMC Systems Biology
Rosa D Hernansaiz-Ballesteros, Luca Cardelli, Attila Csikász-Nagy
BACKGROUND: Switch-like and oscillatory dynamical systems are widely observed in biology. We investigate the simplest biological switch that is composed of a single molecule that can be autocatalytically converted between two opposing activity forms. We test how this simple network can keep its switching behaviour under perturbations in the system. RESULTS: We show that this molecule can work as a robust bistable system, even for alterations in the reactions that drive the switching between various conformations...
June 18, 2018: BMC Systems Biology
Colin P McNally, Elhanan Borenstein
BACKGROUND: Metabolic dependencies between microbial species have a significant impact on the assembly and activity of microbial communities. However, the evolutionary origins of such dependencies and the impact of metabolic and genomic architecture on their emergence are not clear. RESULTS: To address these questions, we developed a novel framework, coupling a reductive evolution model with a multi-species genome-scale metabolic model to simulate the evolution of two-species microbial communities...
June 15, 2018: BMC Systems Biology
Stefano Casagranda, Suzanne Touzeau, Delphine Ropers, Jean-Luc Gouzé
BACKGROUND: Understanding the dynamical behaviour of biological systems is challenged by their large number of components and interactions. While efforts have been made in this direction to reduce model complexity, they often prove insufficient to grasp which and when model processes play a crucial role. Answering these questions is fundamental to unravel the functioning of living organisms. RESULTS: We design a method for dealing with model complexity, based on the analysis of dynamical models by means of Principal Process Analysis...
June 14, 2018: BMC Systems Biology
Chunhe Li, Lei Zhang, Qing Nie
BACKGROUND: Spatial pattern formation is a critical issue in developmental biology. Gene expression boundary sharpening has been observed from both experiments and modeling simulations. However, the mechanism to determine the sharpness of the boundary is not fully elucidated. RESULTS: We investigated the boundary sharpening resulted by three biological motifs, interacting with morphogens, and uncovered their probabilistic landscapes. The landscape view, along with calculated average switching time between attractors, provides a natural explanation for the boundary sharpening behavior relying on the noise induced gene state switchings...
June 13, 2018: BMC Systems Biology
Xin Fang, Jonathan M Monk, Nathan Mih, Bin Du, Anand V Sastry, Erol Kavvas, Yara Seif, Larry Smarr, Bernhard O Palsson
BACKGROUND: Escherichia coli is considered a leading bacterial trigger of inflammatory bowel disease (IBD). E. coli isolates from IBD patients primarily belong to phylogroup B2. Previous studies have focused on broad comparative genomic analysis of E. coli B2 isolates, and identified virulence factors that allow B2 strains to reside within human intestinal mucosa. Metabolic capabilities of E. coli strains have been shown to be related to their colonization site, but remain unexplored in IBD-associated strains...
June 11, 2018: BMC Systems Biology
Marcus Thomas, Russell Schwartz
BACKGROUND: The ability of collections of molecules to spontaneously assemble into large functional complexes is central to all cellular processes. Using the viral capsid as a model system for complicated macro-molecular assembly, we develop methods for probing fine details of the process by learning kinetic rate parameters consistent with experimental measures of assembly. We have previously shown that local rule based stochastic simulation methods in conjunction with bulk indirect experimental data can meaningfully constrain the space of possible assembly trajectories and allow inference of experimentally unobservable features of the real system...
June 8, 2018: BMC Systems Biology
Brian C Ross, Mayla Boguslav, Holly Weeks, James C Costello
BACKGROUND: Certain biological processes, such as the development of cancer and immune activation, can be controlled by rare cellular events that are difficult to capture computationally through simulations of individual cells. Information about such rare events can be gleaned from an attractor analysis, for which a variety of methods exist (in particular for Boolean models). However, explicitly simulating a defined mixed population of cells in a way that tracks even the rarest subpopulations remains an open challenge...
June 7, 2018: BMC Systems Biology
Carlos Vazquez-Hernandez, Antonio Loza, Esteban Peguero-Sanchez, Lorenzo Segovia, Rosa-Maria Gutierrez-Rios
BACKGROUND: Metabolic reactions are chemical transformations commonly catalyzed by enzymes. In recent years, the explosion of genomic data and individual experimental characterizations have contributed to the construction of databases and methodologies for the analysis of metabolic networks. Some methodologies based on graph theory organize compound networks into metabolic functional categories without preserving biochemical pathways. Other methods based on chemical group exchange and atom flow trace the conversion of substrates into products in detail, which is useful for inferring metabolic pathways...
May 30, 2018: BMC Systems Biology
Claudia C Preston, Saranya P Wyles, Santiago Reyes, Emily C Storm, Bruce W Eckloff, Randolph S Faustino
BACKGROUND: Atrial fibrillation is a cardiac disease driven by numerous idiopathic etiologies. NUP155 is a nuclear pore complex protein that has been identified as a clinical driver of atrial fibrillation, yet the precise mechanism is unknown. The present study employs a systems biology algorithm to identify effects of NUP155 disruption on cardiogenicity in a model of stem cell-derived differentiation. METHODS: Embryonic stem (ES) cell lines (n = 5) with truncated NUP155 were cultured in parallel with wild type (WT) ES cells (n = 5), and then harvested for RNAseq...
May 30, 2018: BMC Systems Biology
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