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BMC Systems Biology

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https://www.readbyqxmd.com/read/28302111/quantifying-the-roles-of-random-motility-and-directed-motility-using-advection-diffusion-theory-for-a-3t3-fibroblast-cell-migration-assay-stimulated-with-an-electric-field
#1
Matthew J Simpson, Kai-Yin Lo, Yung-Shin Sun
BACKGROUND: Directed cell migration can be driven by a range of external stimuli, such as spatial gradients of: chemical signals (chemotaxis); adhesion sites (haptotaxis); or temperature (thermotaxis). Continuum models of cell migration typically include a diffusion term to capture the undirected component of cell motility and an advection term to capture the directed component of cell motility. However, there is no consensus in the literature about the form that the advection term takes...
March 17, 2017: BMC Systems Biology
https://www.readbyqxmd.com/read/28298210/delineating-functional-principles-of-the-bow-tie-structure-of-a-kinase-phosphatase-network-in-the-budding-yeast
#2
Diala Abd-Rabbo, Stephen W Michnick
BACKGROUND: Kinases and phosphatases (KP) form complex self-regulating networks essential for cellular signal processing. In spite of having a wealth of data about interactions among KPs and their substrates, we have very limited models of the structures of the directed networks they form and consequently our ability to formulate hypotheses about how their structure determines the flow of information in these networks is restricted. RESULTS: We assembled and studied the largest bona fide kinase-phosphatase network (KP-Net) known to date for the yeast Saccharomyces cerevisiae...
March 16, 2017: BMC Systems Biology
https://www.readbyqxmd.com/read/28298218/systematic-identification-of-an-integrative-network-module-during-senescence-from-time-series-gene-expression
#3
Chihyun Park, So Jeong Yun, Sung Jin Ryu, Soyoung Lee, Young-Sam Lee, Youngmi Yoon, Sang Chul Park
BACKGROUND: Cellular senescence irreversibly arrests growth of human diploid cells. In addition, recent studies have indicated that senescence is a multi-step evolving process related to important complex biological processes. Most studies analyzed only the genes and their functions representing each senescence phase without considering gene-level interactions and continuously perturbed genes. It is necessary to reveal the genotypic mechanism inferred by affected genes and their interaction underlying the senescence process...
March 15, 2017: BMC Systems Biology
https://www.readbyqxmd.com/read/28298216/network-reconstruction-of-the-mouse-secretory-pathway-applied-on-cho-cell-transcriptome-data
#4
Anne Mathilde Lund, Christian Schrøder Kaas, Julian Brandl, Lasse Ebdrup Pedersen, Helene Faustrup Kildegaard, Claus Kristensen, Mikael Rørdam Andersen
BACKGROUND: Protein secretion is one of the most important processes in eukaryotes. It is based on a highly complex machinery involving numerous proteins in several cellular compartments. The elucidation of the cell biology of the secretory machinery is of great importance, as it drives protein expression for biopharmaceutical industry, a 140 billion USD global market. However, the complexity of secretory process is difficult to describe using a simple reductionist approach, and therefore a promising avenue is to employ the tools of systems biology...
March 15, 2017: BMC Systems Biology
https://www.readbyqxmd.com/read/28284215/physiological-fidelity-or-model-parsimony-the-relative-performance-of-reverse-toxicokinetic-modeling-approaches
#5
Michael A Rowland, Edward J Perkins, Michael L Mayo
BACKGROUND: Physiologically-based toxicokinetic (PBTK) models are often developed to facilitate in vitro to in vivo extrapolation (IVIVE) using a top-down, compartmental approach, favoring architectural simplicity over physiological fidelity despite the lack of general guidelines relating model design to dynamical predictions. Here we explore the impact of design choice (high vs. low fidelity) on chemical distribution throughout an animal's organ system. RESULTS: We contrast transient dynamics and steady states of three previously proposed PBTK models of varying complexity in response to chemical exposure...
March 11, 2017: BMC Systems Biology
https://www.readbyqxmd.com/read/28284213/mathematical-modelling-and-a-systems-science-approach-to-describe-the-role-of-cytokines-in-the-evolution-of-severe-dengue
#6
S D Pavithra Jayasundara, S S N Perera, Gathsaurie Neelika Malavige, Saroj Jayasinghe
BACKGROUND: Dengue causes considerable morbidity and mortality in Sri Lanka. Inflammatory mediators such as cytokines, contribute to its evolution from an asymptotic infection to severe forms of dengue. The majority of previous studies have analysed the association of individual cytokines with clinical disease severity. In contrast, we view evolution to Dengue Haemorrhagic Fever as the behaviour of a complex dynamic system. We therefore, analyse the combined effect of multiple cytokines that interact dynamically with each other in order to generate a mathematical model to predict occurrence of Dengue Haemorrhagic Fever...
March 11, 2017: BMC Systems Biology
https://www.readbyqxmd.com/read/28270142/dynamic-proteomics-reveals-bimodal-protein-dynamics-of-cancer-cells-in-response-to-hsp90-inhibitor
#7
Anat Zimmer, Shlomit Amar-Farkash, Tamar Danon, Uri Alon
BACKGROUND: Drugs often kill some cancer cells while others survive. This stochastic outcome is seen even in clonal cells grown under the same conditions. Understanding the molecular reasons for this stochastic outcome is a current challenge, which requires studying the proteome at the single cell level over time. In a previous study we used dynamic proteomics to study the response of cancer cells to a DNA damaging drug, camptothecin. Several proteins showed bimodal dynamics: they rose in some cells and decreased in others, in a way that correlated with eventual cell fate: death or survival...
March 7, 2017: BMC Systems Biology
https://www.readbyqxmd.com/read/28259158/detection-of-statistically-significant-network-changes-in-complex-biological-networks
#8
Raghvendra Mall, Luigi Cerulo, Halima Bensmail, Antonio Iavarone, Michele Ceccarelli
BACKGROUND: Biological networks contribute effectively to unveil the complex structure of molecular interactions and to discover driver genes especially in cancer context. It can happen that due to gene mutations, as for example when cancer progresses, the gene expression network undergoes some amount of localized re-wiring. The ability to detect statistical relevant changes in the interaction patterns induced by the progression of the disease can lead to the discovery of novel relevant signatures...
March 4, 2017: BMC Systems Biology
https://www.readbyqxmd.com/read/28249581/systems-biology-combining-human-and-animal-data-mirna-and-mrna-data-identifies-new-targets-in-ureteropelvic-junction-obstruction
#9
Theofilos Papadopoulos, Audrey Casemayou, Eric Neau, Benjamin Breuil, Cécile Caubet, Denis Calise, Barbara A Thornhill, Magdalena Bachvarova, Julie Belliere, Robert L Chevalier, Panagiotis Moulos, Dimcho Bachvarov, Benedicte Buffin-Meyer, Stéphane Decramer, Françoise Conte Auriol, Jean-Loup Bascands, Joost P Schanstra, Julie Klein
BACKGROUND: Although renal fibrosis and inflammation have shown to be involved in the pathophysiology of obstructive nephropathies, molecular mechanisms underlying evolution of these processes remain undetermined. In an attempt towards improved understanding of obstructive nephropathy and improved translatability of the results to clinical practice we have developed a systems biology approach combining omics data of both human and mouse obstructive nephropathy. RESULTS: We have studied in parallel the urinary miRNome of infants with ureteropelvic junction obstruction and the kidney tissue miRNome and transcriptome of the corresponding neonatal partial unilateral ureteral obstruction (UUO) mouse model...
March 1, 2017: BMC Systems Biology
https://www.readbyqxmd.com/read/28241833/predicting-network-modules-of-cell-cycle-regulators-using-relative-protein-abundance-statistics
#10
Cihan Oguz, Layne T Watson, William T Baumann, John J Tyson
BACKGROUND: Parameter estimation in systems biology is typically done by enforcing experimental observations through an objective function as the parameter space of a model is explored by numerical simulations. Past studies have shown that one usually finds a set of "feasible" parameter vectors that fit the available experimental data equally well, and that these alternative vectors can make different predictions under novel experimental conditions. In this study, we characterize the feasible region of a complex model of the budding yeast cell cycle under a large set of discrete experimental constraints in order to test whether the statistical features of relative protein abundance predictions are influenced by the topology of the cell cycle regulatory network...
February 28, 2017: BMC Systems Biology
https://www.readbyqxmd.com/read/28235406/network-topology-of-nav1-7-mutations-in-sodium-channel-related-painful-disorders
#11
Dimos Kapetis, Jenny Sassone, Yang Yang, Barbara Galbardi, Markos N Xenakis, Ronald L Westra, Radek Szklarczyk, Patrick Lindsey, Catharina G Faber, Monique Gerrits, Ingemar S J Merkies, Sulayman D Dib-Hajj, Massimo Mantegazza, Stephen G Waxman, Giuseppe Lauria
BACKGROUND: Gain-of-function mutations in SCN9A gene that encodes the voltage-gated sodium channel NaV1.7 have been associated with a wide spectrum of painful syndromes in humans including inherited erythromelalgia, paroxysmal extreme pain disorder and small fibre neuropathy. These mutations change the biophysical properties of NaV1.7 channels leading to hyperexcitability of dorsal root ganglion nociceptors and pain symptoms. There is a need for better understanding of how gain-of-function mutations alter the atomic structure of Nav1...
February 24, 2017: BMC Systems Biology
https://www.readbyqxmd.com/read/28235404/progesterone-signalling-in-broiler-skeletal-muscle-is-associated-with-divergent-feed-efficiency
#12
Walter Bottje, Byung-Whi Kong, Antonio Reverter, Ashley J Waardenberg, Kentu Lassiter, Nicholas J Hudson
BACKGROUND: We contrast the pectoralis muscle transcriptomes of broilers selected from within a single genetic line expressing divergent feed efficiency (FE) in an effort to improve our understanding of the mechanistic basis of FE. RESULTS: Application of a virtual muscle model to gene expression data pointed to a coordinated reduction in slow twitch muscle isoforms of the contractile apparatus (MYH15, TPM3, MYOZ2, TNNI1, MYL2, MYOM3, CSRP3, TNNT2), consistent with diminishment in associated slow machinery (myoglobin and phospholamban) in the high FE animals...
February 24, 2017: BMC Systems Biology
https://www.readbyqxmd.com/read/28222737/dynamic-genome-scale-metabolic-modeling-of-the-yeast-pichia-pastoris
#13
Francisco Saitua, Paulina Torres, José Ricardo Pérez-Correa, Eduardo Agosin
BACKGROUND: Pichia pastoris shows physiological advantages in producing recombinant proteins, compared to other commonly used cell factories. This yeast is mostly grown in dynamic cultivation systems, where the cell's environment is continuously changing and many variables influence process productivity. In this context, a model capable of explaining and predicting cell behavior for the rational design of bioprocesses is highly desirable. Currently, there are five genome-scale metabolic reconstructions of P...
February 21, 2017: BMC Systems Biology
https://www.readbyqxmd.com/read/28219373/a-new-efficient-approach-to-fit-stochastic-models-on-the-basis-of-high-throughput-experimental-data-using-a-model-of-irf7-gene-expression-as-case-study
#14
Luis U Aguilera, Christoph Zimmer, Ursula Kummer
BACKGROUND: Mathematical models are used to gain an integrative understanding of biochemical processes and networks. Commonly the models are based on deterministic ordinary differential equations. When molecular counts are low, stochastic formalisms like Monte Carlo simulations are more appropriate and well established. However, compared to the wealth of computational methods used to fit and analyze deterministic models, there is only little available to quantify the exactness of the fit of stochastic models compared to experimental data or to analyze different aspects of the modeling results...
February 20, 2017: BMC Systems Biology
https://www.readbyqxmd.com/read/28209199/making-life-difficult-for-clostridium-difficile-augmenting-the-pathogen-s-metabolic-model-with-transcriptomic-and-codon-usage-data-for-better-therapeutic-target-characterization
#15
Sara Saheb Kashaf, Claudio Angione, Pietro Lió
BACKGROUND: Clostridium difficile is a bacterium which can infect various animal species, including humans. Infection with this bacterium is a leading healthcare-associated illness. A better understanding of this organism and the relationship between its genotype and phenotype is essential to the search for an effective treatment. Genome-scale metabolic models contain all known biochemical reactions of a microorganism and can be used to investigate this relationship. RESULTS: We present icdf834, an updated metabolic network of C...
February 16, 2017: BMC Systems Biology
https://www.readbyqxmd.com/read/28209158/gene-regulatory-network-underlying-the-immortalization-of-epithelial-cells
#16
Luis Fernando Méndez-López, Jose Davila-Velderrain, Elisa Domínguez-Hüttinger, Christian Enríquez-Olguín, Juan Carlos Martínez-García, Elena R Alvarez-Buylla
BACKGROUND: Tumorigenic transformation of human epithelial cells in vitro has been described experimentally as the potential result of spontaneous immortalization. This process is characterized by a series of cell-state transitions, in which normal epithelial cells acquire first a senescent state which is later surpassed to attain a mesenchymal stem-like phenotype with a potentially tumorigenic behavior. In this paper we aim to provide a system-level mechanistic explanation to the emergence of these cell types, and to the time-ordered transition patterns that are common to neoplasias of epithelial origin...
February 16, 2017: BMC Systems Biology
https://www.readbyqxmd.com/read/28193218/a-combined-model-reduction-algorithm-for-controlled-biochemical-systems
#17
Thomas J Snowden, Piet H van der Graaf, Marcus J Tindall
BACKGROUND: Systems Biology continues to produce increasingly large models of complex biochemical reaction networks. In applications requiring, for example, parameter estimation, the use of agent-based modelling approaches, or real-time simulation, this growing model complexity can present a significant hurdle. Often, however, not all portions of a model are of equal interest in a given setting. In such situations methods of model reduction offer one possible approach for addressing the issue of complexity by seeking to eliminate those portions of a pathway that can be shown to have the least effect upon the properties of interest...
February 13, 2017: BMC Systems Biology
https://www.readbyqxmd.com/read/28166778/markov-state-models-of-gene-regulatory-networks
#18
Brian K Chu, Margaret J Tse, Royce R Sato, Elizabeth L Read
BACKGROUND: Gene regulatory networks with dynamics characterized by multiple stable states underlie cell fate-decisions. Quantitative models that can link molecular-level knowledge of gene regulation to a global understanding of network dynamics have the potential to guide cell-reprogramming strategies. Networks are often modeled by the stochastic Chemical Master Equation, but methods for systematic identification of key properties of the global dynamics are currently lacking. RESULTS: The method identifies the number, phenotypes, and lifetimes of long-lived states for a set of common gene regulatory network models...
February 6, 2017: BMC Systems Biology
https://www.readbyqxmd.com/read/28153012/kinetic-stability-analysis-of-protein-assembly-on-the-center-manifold-around-the-critical-point
#19
Tatsuaki Tsuruyama
BACKGROUND: Non-linear kinetic analysis is a useful method for illustration of the dynamic behavior of cellular biological systems. To date, center manifold theory (CMT) has not been sufficiently applied for stability analysis of biological systems. The aim of this study is to demonstrate the application of CMT to kinetic analysis of protein assembly and disassembly, and to propose a novel framework for nonlinear multi-parametric analysis. We propose a protein assembly model with nonlinear kinetics provided by the fluctuation in monomer concentrations during their diffusion...
February 2, 2017: BMC Systems Biology
https://www.readbyqxmd.com/read/28137253/the-integration-of-weighted-human-gene-association-networks-based-on-link-prediction
#20
Jian Yang, Tinghong Yang, Duzhi Wu, Limei Lin, Fan Yang, Jing Zhao
BACKGROUND: Physical and functional interplays between genes or proteins have important biological meaning for cellular functions. Some efforts have been made to construct weighted gene association meta-networks by integrating multiple biological resources, where the weight indicates the confidence of the interaction. However, it is found that these existing human gene association networks share only quite limited overlapped interactions, suggesting their incompleteness and noise. RESULTS: Here we proposed a workflow to construct a weighted human gene association network using information of six existing networks, including two weighted specific PPI networks and four gene association meta-networks...
January 31, 2017: BMC Systems Biology
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