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BMC Systems Biology

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https://www.readbyqxmd.com/read/27899149/the-quality-of-metabolic-pathway-resources-depends-on-initial-enzymatic-function-assignments-a-case-for-maize
#1
Jesse R Walsh, Mary L Schaeffer, Peifen Zhang, Seung Y Rhee, Julie A Dickerson, Taner Z Sen
BACKGROUND: As metabolic pathway resources become more commonly available, researchers have unprecedented access to information about their organism of interest. Despite efforts to ensure consistency between various resources, information content and quality can vary widely. Two maize metabolic pathway resources for the B73 inbred line, CornCyc 4.0 and MaizeCyc 2.2, are based on the same gene model set and were developed using Pathway Tools software. These resources differ in their initial enzymatic function assignments and in the extent of manual curation...
November 29, 2016: BMC Systems Biology
https://www.readbyqxmd.com/read/27884189/sparse-improved-event-based-stochastic-parameter-search
#2
Min K Roh, Bernie J Daigle
BACKGROUND: Despite the increasing availability of high performance computing capabilities, analysis and characterization of stochastic biochemical systems remain a computational challenge. To address this challenge, the Stochastic Parameter Search for Events (SParSE) was developed to automatically identify reaction rates that yield a probabilistic user-specified event. SParSE consists of three main components: the multi-level cross-entropy method, which identifies biasing parameters to push the system toward the event of interest, the related inverse biasing method, and an optional interpolation of identified parameters...
November 25, 2016: BMC Systems Biology
https://www.readbyqxmd.com/read/27884151/unearthing-the-transition-rates-between-photoreceptor-conformers
#3
Robert W Smith, Britta Helwig, Adrie H Westphal, Eran Pel, Maximilian Hörner, Hannes M Beyer, Sophia L Samodelov, Wilfried Weber, Matias D Zurbriggen, Jan Willem Borst, Christian Fleck
BACKGROUND: Obtaining accurate estimates of biological or enzymatic reaction rates is critical in understanding the design principles of a network and how biological processes can be experimentally manipulated on demand. In many cases experimental limitations mean that some enzymatic rates cannot be measured directly, requiring mathematical algorithms to estimate them. Here, we describe a methodology that calculates rates at which light-regulated proteins switch between conformational states...
November 25, 2016: BMC Systems Biology
https://www.readbyqxmd.com/read/27863488/mathematical-model-on-alzheimer-s-disease
#4
Wenrui Hao, Avner Friedman
BACKGROUND: Alzheimer disease (AD) is a progressive neurodegenerative disease that destroys memory and cognitive skills. AD is characterized by the presence of two types of neuropathological hallmarks: extracellular plaques consisting of amyloid β-peptides and intracellular neurofibrillary tangles of hyperphosphorylated tau proteins. The disease affects 5 million people in the United States and 44 million world-wide. Currently there is no drug that can cure, stop or even slow the progression of the disease...
November 18, 2016: BMC Systems Biology
https://www.readbyqxmd.com/read/27846901/a-method-for-automated-pathogenic-content-estimation-with-application-to-rheumatoid-arthritis
#5
Xiaoyuan Zhou, Christine Nardini
BACKGROUND: Sequencing technologies applied to mammals' microbiomes have revolutionized our understanding of health and disease. Hence, to assess diseases' progression as well as therapies longterm effects, the impact of maladies and drugs on the gut-intestinal (GI) microbiome has to be evaluated. Typical metagenomic analyses are run to associate to a condition (disease, therapy, diet) a pool of bacteria, whose eubiotic/dysbiotic potential is assessed either by α-diversity, a measure of the varieties populating the microbiome, or by Firmicutes to Bacteroides ratio, associated to systemic inflammation, and finally by manual and direct inspection of bacteria's biological functions, when known...
November 15, 2016: BMC Systems Biology
https://www.readbyqxmd.com/read/27846853/dgca-a-comprehensive-r-package-for-differential-gene-correlation-analysis
#6
Andrew T McKenzie, Igor Katsyv, Won-Min Song, Minghui Wang, Bin Zhang
BACKGROUND: Dissecting the regulatory relationships between genes is a critical step towards building accurate predictive models of biological systems. A powerful approach towards this end is to systematically study the differences in correlation between gene pairs in more than one distinct condition. RESULTS: In this study we develop an R package, DGCA (for Differential Gene Correlation Analysis), which offers a suite of tools for computing and analyzing differential correlations between gene pairs across multiple conditions...
November 15, 2016: BMC Systems Biology
https://www.readbyqxmd.com/read/27846849/untargeted-metabolomics-unravels-functionalities-of-phosphorylation-sites-in-saccharomyces-cerevisiae
#7
Zrinka Raguz Nakic, Gerhard Seisenbacher, Francesc Posas, Uwe Sauer
BACKGROUND: Coordinated through a complex network of kinases and phosphatases, protein phosphorylation regulates essentially all cellular processes in eukaryotes. Recent advances in proteomics enable detection of thousands of phosphorylation sites (phosphosites) in single experiments. However, functionality of the vast majority of these sites remains unclear and we lack suitable approaches to evaluate functional relevance at a pace that matches their detection. RESULTS: Here, we assess functionality of 26 phosphosites by introducing phosphodeletion and phosphomimic mutations in 25 metabolic enzymes and regulators from the TOR and HOG signaling pathway in Saccharomyces cerevisiae by phenotypic analysis and untargeted metabolomics...
November 15, 2016: BMC Systems Biology
https://www.readbyqxmd.com/read/27846841/integrative-transcriptome-network-analysis-of-ipsc-derived-neurons-from-schizophrenia-and-schizoaffective-disorder-patients-with-22q11-2-deletion
#8
Mingyan Lin, Erika Pedrosa, Anastasia Hrabovsky, Jian Chen, Benjamin R Puliafito, Stephanie R Gilbert, Deyou Zheng, Herbert M Lachman
BACKGROUND: Individuals with 22q11.2 Deletion Syndrome (22q11.2 DS) are a specific high-risk group for developing schizophrenia (SZ), schizoaffective disorder (SAD) and autism spectrum disorders (ASD). Several genes in the deleted region have been implicated in the development of SZ, e.g., PRODH and DGCR8. However, the mechanistic connection between these genes and the neuropsychiatric phenotype remains unclear. To elucidate the molecular consequences of 22q11.2 deletion in early neural development, we carried out RNA-seq analysis to investigate gene expression in early differentiating human neurons derived from induced pluripotent stem cells (iPSCs) of 22q11...
November 15, 2016: BMC Systems Biology
https://www.readbyqxmd.com/read/27814699/in-silico-identification-of-essential-proteins-in-corynebacterium-pseudotuberculosis-based-on-protein-protein-interaction-networks
#9
Edson Luiz Folador, Paulo Vinícius Sanches Daltro de Carvalho, Wanderson Marques Silva, Rafaela Salgado Ferreira, Artur Silva, Michael Gromiha, Preetam Ghosh, Debmalya Barh, Vasco Azevedo, Richard Röttger
BACKGROUND: Corynebacterium pseudotuberculosis (Cp) is a gram-positive bacterium that is classified into equi and ovis serovars. The serovar ovis is the etiological agent of caseous lymphadenitis, a chronic infection affecting sheep and goats, causing economic losses due to carcass condemnation and decreased production of meat, wool, and milk. Current diagnosis or treatment protocols are not fully effective and, thus, require further research of Cp pathogenesis. RESULTS: Here, we mapped known protein-protein interactions (PPI) from various species to nine Cp strains to reconstruct parts of the potential Cp interactome and to identify potentially essential proteins serving as putative drug targets...
November 4, 2016: BMC Systems Biology
https://www.readbyqxmd.com/read/27793154/in-silico-metabolic-network-analysis-of-arabidopsis-leaves
#10
Veronique Beckers, Lisa Maria Dersch, Katrin Lotz, Guido Melzer, Oliver Ernst Bläsing, Regine Fuchs, Thomas Ehrhardt, Christoph Wittmann
BACKGROUND: During the last decades, we face an increasing interest in superior plants to supply growing demands for human and animal nutrition and for the developing bio-based economy. Presently, our limited understanding of their metabolism and its regulation hampers the targeted development of desired plant phenotypes. In this regard, systems biology, in particular the integration of metabolic and regulatory networks, is promising to broaden our knowledge and to further explore the biotechnological potential of plants...
October 29, 2016: BMC Systems Biology
https://www.readbyqxmd.com/read/27770812/combining-laboratory-and-mathematical-models-to-infer-mechanisms-underlying-kinetic-changes-in-macrophage-susceptibility-to-an-rna-virus
#11
Andrea Doeschl-Wilson, Alison Wilson, Jens Nielsen, Hans Nauwynck, Alan Archibald, Tahar Ait-Ali
BACKGROUND: Macrophages are essential to innate immunity against many pathogens, but some pathogens also target macrophages as routes to infection. The Porcine Reproductive and Respiratory Syndrome virus (PRRSV) is an RNA virus that infects porcine alveolar macrophages (PAMs) causing devastating impact on global pig production. Identifying the cellular mechanisms that mediate PAM susceptibility to the virus is crucial for developing effective interventions. Previous evidence suggests that the scavenger receptor CD163 is essential for productive infection of PAMs with PRRSV...
October 22, 2016: BMC Systems Biology
https://www.readbyqxmd.com/read/27769280/generalized-method-of-moments-for-estimating-parameters-of-stochastic-reaction-networks
#12
Alexander Lück, Verena Wolf
BACKGROUND: Discrete-state stochastic models have become a well-established approach to describe biochemical reaction networks that are influenced by the inherent randomness of cellular events. In the last years several methods for accurately approximating the statistical moments of such models have become very popular since they allow an efficient analysis of complex networks. RESULTS: We propose a generalized method of moments approach for inferring the parameters of reaction networks based on a sophisticated matching of the statistical moments of the corresponding stochastic model and the sample moments of population snapshot data...
October 21, 2016: BMC Systems Biology
https://www.readbyqxmd.com/read/27769272/erratum-to-a-novel-mathematical-model-of-atm-p53-nf-%C3%AE%C2%BAb-pathways-points-to-the-importance-of-the-ddr-switch-off-mechanisms
#13
Katarzyna Jonak, Monika Kurpas, Katarzyna Szoltysek, Patryk Janus, Agata Abramowicz, Krzysztof Puszynski
No abstract text is available yet for this article.
October 21, 2016: BMC Systems Biology
https://www.readbyqxmd.com/read/27769243/the-potential-for-non-adaptive-origins-of-evolutionary-innovations-in-central-carbon-metabolism
#14
Sayed-Rzgar Hosseini, Andreas Wagner
BACKGROUND: Biological systems are rife with examples of pre-adaptations or exaptations. They range from the molecular scale - lens crystallins, which originated from metabolic enzymes - to the macroscopic scale, such as feathers used in flying, which originally served thermal insulation or waterproofing. An important class of exaptations are novel and useful traits with non-adaptive origins. Whether such origins could be frequent cannot be answered with individual examples, because it is a question about a biological system's potential for exaptation...
October 21, 2016: BMC Systems Biology
https://www.readbyqxmd.com/read/27769238/bcm-toolkit-for-bayesian-analysis-of-computational-models-using-samplers
#15
Bram Thijssen, Tjeerd M H Dijkstra, Tom Heskes, Lodewyk F A Wessels
BACKGROUND: Computational models in biology are characterized by a large degree of uncertainty. This uncertainty can be analyzed with Bayesian statistics, however, the sampling algorithms that are frequently used for calculating Bayesian statistical estimates are computationally demanding, and each algorithm has unique advantages and disadvantages. It is typically unclear, before starting an analysis, which algorithm will perform well on a given computational model. RESULTS: We present BCM, a toolkit for the Bayesian analysis of Computational Models using samplers...
October 21, 2016: BMC Systems Biology
https://www.readbyqxmd.com/read/27765040/attractor-landscape-analysis-of-colorectal-tumorigenesis-and-its-reversion
#16
Sung-Hwan Cho, Sang-Min Park, Ho-Sung Lee, Hwang-Yeol Lee, Kwang-Hyun Cho
BACKGROUND: Colorectal cancer arises from the accumulation of genetic mutations that induce dysfunction of intracellular signaling. However, the underlying mechanism of colorectal tumorigenesis driven by genetic mutations remains yet to be elucidated. RESULTS: To investigate colorectal tumorigenesis at a system-level, we have reconstructed a large-scale Boolean network model of the human signaling network by integrating previous experimental results on canonical signaling pathways related to proliferation, metastasis, and apoptosis...
October 20, 2016: BMC Systems Biology
https://www.readbyqxmd.com/read/27717349/an-efficient-algorithm-for-identifying-primary-phenotype-attractors-of-a-large-scale-boolean-network
#17
Sang-Mok Choo, Kwang-Hyun Cho
BACKGROUND: Boolean network modeling has been widely used to model large-scale biomolecular regulatory networks as it can describe the essential dynamical characteristics of complicated networks in a relatively simple way. When we analyze such Boolean network models, we often need to find out attractor states to investigate the converging state features that represent particular cell phenotypes. This is, however, very difficult (often impossible) for a large network due to computational complexity...
October 7, 2016: BMC Systems Biology
https://www.readbyqxmd.com/read/27663205/the-effect-of-inhibition-of-pp1-and-tnf%C3%AE-signaling-on-pathogenesis-of-sars-coronavirus
#18
Jason E McDermott, Hugh D Mitchell, Lisa E Gralinski, Amie J Eisfeld, Laurence Josset, Armand Bankhead, Gabriele Neumann, Susan C Tilton, Alexandra Schäfer, Chengjun Li, Shufang Fan, Shannon McWeeney, Ralph S Baric, Michael G Katze, Katrina M Waters
BACKGROUND: The complex interplay between viral replication and host immune response during infection remains poorly understood. While many viruses are known to employ anti-immune strategies to facilitate their replication, highly pathogenic virus infections can also cause an excessive immune response that exacerbates, rather than reduces pathogenicity. To investigate this dichotomy in severe acute respiratory syndrome coronavirus (SARS-CoV), we developed a transcriptional network model of SARS-CoV infection in mice and used the model to prioritize candidate regulatory targets for further investigation...
September 23, 2016: BMC Systems Biology
https://www.readbyqxmd.com/read/27662842/identification-of-control-targets-in-boolean-molecular-network-models-via-computational-algebra
#19
David Murrugarra, Alan Veliz-Cuba, Boris Aguilar, Reinhard Laubenbacher
BACKGROUND: Many problems in biomedicine and other areas of the life sciences can be characterized as control problems, with the goal of finding strategies to change a disease or otherwise undesirable state of a biological system into another, more desirable, state through an intervention, such as a drug or other therapeutic treatment. The identification of such strategies is typically based on a mathematical model of the process to be altered through targeted control inputs. This paper focuses on processes at the molecular level that determine the state of an individual cell, involving signaling or gene regulation...
September 23, 2016: BMC Systems Biology
https://www.readbyqxmd.com/read/27655224/quantifying-differences-in-cell-line-population-dynamics-using-cellpd
#20
Edwin F Juarez, Roy Lau, Samuel H Friedman, Ahmadreza Ghaffarizadeh, Edmond Jonckheere, David B Agus, Shannon M Mumenthaler, Paul Macklin
BACKGROUND: The increased availability of high-throughput datasets has revealed a need for reproducible and accessible analyses which can quantitatively relate molecular changes to phenotypic behavior. Existing tools for quantitative analysis generally require expert knowledge. RESULTS: CellPD (cell phenotype digitizer) facilitates quantitative phenotype analysis, allowing users to fit mathematical models of cell population dynamics without specialized training...
September 21, 2016: BMC Systems Biology
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