%0 Journal Article %A Smedley, D. %A Swertz, M. A. %A Wolstencroft, K. %A Proctor, G. %A Zouberakis, M. %A Bard, J. %A Hancock, J. M. %A Schofield, P. %D 2008 %T Solutions for data integration in functional genomics: a critical assessment and case study. %J Brief Bioinform %V 9 %N 6 %P 532-544 %M 19112082 %U http://www.ncbi.nlm.nih.gov/pubmed/19112082 %X The torrent of data emerging from the application of new technologies to functional genomics and systems biology can no longer be contained within the traditional modes of data sharing and publication with the consequence that data is being deposited in, distributed across and disseminated through an increasing number of databases. The resulting fragmentation poses serious problems for the model organism community which increasingly rely on data mining and computational approaches that require gathering of data from a range of sources. In the light of these problems, the European Commission has funded a coordination action, CASIMIR (coordination and sustainability of international mouse informatics resources), with a remit to assess the technical and social aspects of database interoperability that currently prevent the full realization of the potential of data integration in mouse functional genomics. In this article, we assess the current problems with interoperability, with particular reference to mouse functional genomics, and critically review the technologies that can be deployed to overcome them. We describe a typical use-case where an investigator wishes to gather data on variation, genomic context and metabolic pathway involvement for genes discovered in a genome-wide screen. We go on to develop an automated approach involving an in silico experimental workflow tool, Taverna, using web services, BioMart and MOLGENIS technologies for data retrieval. Finally, we focus on the current impediments to adopting such an approach in a wider context, and strategies to overcome them. %K Animals %K Computational Biology/*methods %K *Database Management Systems %K *Databases, Genetic %K Genomics/*methods %K Humans %K Information Storage and Retrieval %K Mice %K Software %K User-Computer Interface %+ European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK. damian@ebi.ac.uk. %0 Journal Article %A Fisher, P. %A Hedeler, C. %A Wolstencroft, K. %A Hulme, H. %A Noyes, H. %A Kemp, S. %A Stevens, R. %A Brass, A. %D 2007 %T A systematic strategy for large-scale analysis of genotype phenotype correlations: identification of candidate genes involved in African trypanosomiasis. %J Nucleic Acids Res %V 35 %N 16 %P 5625-5633 %M 17709344 %U http://www.ncbi.nlm.nih.gov/pubmed/17709344 %X It is increasingly common to combine Microarray and Quantitative Trait Loci data to aid the search for candidate genes responsible for phenotypic variation. Workflows provide a means of systematically processing these large datasets and also represent a framework for the re-use and the explicit declaration of experimental methods. In this article, we highlight the issues facing the manual analysis of microarray and QTL data for the discovery of candidate genes underlying complex phenotypes. We show how automated approaches provide a systematic means to investigate genotype-phenotype correlations. This methodology was applied to a use case of resistance to African trypanosomiasis in the mouse. Pathways represented in the results identified Daxx as one of the candidate genes within the Tir1 QTL region. Subsequent re-sequencing in Daxx identified a deletion of an amino acid, identified in susceptible mouse strains, in the Daxx-p53 protein-binding region. This supports recent experimental evidence that apoptosis could be playing a role in the trypanosomiasis resistance phenotype. Workflows developed in this investigation, including a guide to loading and executing them with example data, are available at http://workflows.mygrid.org.uk/repository/myGrid/PaulFisher/. %K Animals %K Base Sequence %K Carrier Proteins/genetics %K Co-Repressor Proteins %K *Gene Expression Profiling %K *Genetic Predisposition to Disease %K Genotype %K Immunity, Innate/genetics %K Intracellular Signaling Peptides and Proteins/genetics %K Mice %K Molecular Chaperones %K Molecular Sequence Data %K Nuclear Proteins/genetics %K Oligonucleotide Array Sequence Analysis %K Phenotype %K *Quantitative Trait Loci %K Sequence Alignment %K Software %K Trypanosomiasis, African/*genetics/metabolism %+ School of Computer Science, Kilburn Building, University of Manchester, Oxford Road, Manchester, UK. pfisher@cs.manchester.ac.uk %0 Journal Article %A Nieselt, K. %A Battke, F. %A Herbig, A. %A Bruheim, P. %A Wentzel, A. %A Jakobsen, O. M. %A Sletta, H. %A Alam, M. T. %A Merlo, M. E. %A Moore, J. %A Omara, W. A. %A Morrissey, E. R. %A Juarez-Hermosillo, M. A. %A Rodriguez-Garcia, A. %A Nentwich, M. %A Thomas, L. %A Iqbal, M. %A Legaie, R. %A Gaze, W. H. %A Challis, G. L. %A Jansen, R. C. %A Dijkhuizen, L. %A Rand, D. A. %A Wild, D. L. %A Bonin, M. %A Reuther, J. %A Wohlleben, W. %A Smith, M. C. %A Burroughs, N. J. %A Martin, J. F. %A Hodgson, D. A. %A Takano, E. %A Breitling, R. %A Ellingsen, T. E. %A Wellington, E. M. %D 2010 %T The dynamic architecture of the metabolic switch in Streptomyces coelicolor. %J BMC Genomics %V 11 %P 10 %M 20053288 %U http://www.ncbi.nlm.nih.gov/pubmed/20053288 %X BACKGROUND: During the lifetime of a fermenter culture, the soil bacterium S. coelicolor undergoes a major metabolic switch from exponential growth to antibiotic production. We have studied gene expression patterns during this switch, using a specifically designed Affymetrix genechip and a high-resolution time-series of fermenter-grown samples. RESULTS: Surprisingly, we find that the metabolic switch actually consists of multiple finely orchestrated switching events. Strongly coherent clusters of genes show drastic changes in gene expression already many hours before the classically defined transition phase where the switch from primary to secondary metabolism was expected. The main switch in gene expression takes only 2 hours, and changes in antibiotic biosynthesis genes are delayed relative to the metabolic rearrangements. Furthermore, global variation in morphogenesis genes indicates an involvement of cell differentiation pathways in the decision phase leading up to the commitment to antibiotic biosynthesis. CONCLUSIONS: Our study provides the first detailed insights into the complex sequence of early regulatory events during and preceding the major metabolic switch in S. coelicolor, which will form the starting point for future attempts at engineering antibiotic production in a biotechnological setting. %K Anti-Bacterial Agents/biosynthesis %K Cluster Analysis %K Fermentation %K *Gene Expression Profiling %K Gene Expression Regulation, Bacterial %K Genes, Bacterial %K Multigene Family %K RNA, Bacterial/genetics %K Streptomyces coelicolor/*genetics/growth & development/*metabolism %+ Center for Bioinformatics Tubingen, Department of Information and Cognitive Sciences, University of Tubingen, D-72076 Tubingen, Germany. nieselt@informatik.uni-tuebingen.de %0 Journal Article %A Krause, F. %A Uhlendorf, J. %A Lubitz, T. %A Schulz, M. %A Klipp, E. %A Liebermeister, W. %D 2010 %T Annotation and merging of SBML models with semanticSBML. %J Bioinformatics %V 26 %N 3 %P 421-422 %M 19933161 %U http://www.ncbi.nlm.nih.gov/pubmed/19933161 %X SUMMARY: Systems Biology Markup Language (SBML) is the leading exchange format for mathematical models in Systems Biology. Semantic annotations link model elements with external knowledge via unique database identifiers and ontology terms, enabling software to check and process models by their biochemical meaning. Such information is essential for model merging, one of the key steps towards the construction of large kinetic models. SemanticSBML is a tool that helps users to check and edit MIRIAM annotations and SBO terms in SBML models. Using a large collection of biochemical names and database identifiers, it supports modellers in finding the right annotations and in merging existing models. Initially, an element matching is derived from the MIRIAM annotations and conflicting element attributes are categorized and highlighted. Conflicts can then be resolved automatically or manually, allowing the user to control the merging process in detail. AVAILABILITY: SemanticSBML comes as a free software written in Python and released under the GPL 3. A Debian package, a source package for other Linux distributions, a Windows installer and an online version of semanticSBML with limited functionality are available at http://www.semanticsbml.org. A preinstalled version can be found on the Linux live DVD SB.OS, available at http://www.sbos.eu. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. %K Computational Biology/*methods %K Database Management Systems %K Databases, Factual %K Semantics %K *Software %K Systems Biology/*methods %+ Theoretische Biophysik, Humboldt-Universitat zu Berlin, Invalidenstrasse 42, D-10115 Berlin, Germany. %0 Journal Article %A Rojas, I. %A Golebiewski, M. %A Kania, R. %A Krebs, O. %A Mir, S. %A Weidemann, A. %A Wittig, U. %D 2007 %T Storing and annotating of kinetic data. %J In Silico Biol %V 7 %N 2 Suppl %P S37-S44 %M 17822389 %U http://www.ncbi.nlm.nih.gov/pubmed/17822389 %X This paper briefly describes the SABIO-RK database model for the storage of reaction kinetics information and the guidelines followed within the SABIO-RK project to annotate the kinetic data. Such annotations support the definition of cross links to other related databases and augment the semantics of the data stored in the database. %K Animals %K *Databases, Protein %K Enzymes/*chemistry %K Humans %K Kinetics %K *Software %K Vocabulary, Controlled %+ Scientific Databases and Visualization Group, EML Research gGmbH, Heidelberg, Germany. isabel.rojas@eml-r.villa-bosch.de %0 Journal Article %A Teusink, B. %A Passarge, J. %A Reijenga, C. A. %A Esgalhado, E. %A van der Weijden, C. C. %A Schepper, M. %A Walsh, M. C. %A Bakker, B. M. %A van Dam, K. %A Westerhoff, H. V. %A Snoep, J. L. %D 2000 %T Can yeast glycolysis be understood in terms of in vitro kinetics of the constituent enzymes? Testing biochemistry. %J Eur J Biochem %V 267 %N 17 %P 5313-5329 %M 10951190 %U http://www.ncbi.nlm.nih.gov/pubmed/10951190 %X This paper examines whether the in vivo behavior of yeast glycolysis can be understood in terms of the in vitro kinetic properties of the constituent enzymes. In nongrowing, anaerobic, compressed Saccharomyces cerevisiae the values of the kinetic parameters of most glycolytic enzymes were determined. For the other enzymes appropriate literature values were collected. By inserting these values into a kinetic model for glycolysis, fluxes and metabolites were calculated. Under the same conditions fluxes and metabolite levels were measured. In our first model, branch reactions were ignored. This model failed to reach the stable steady state that was observed in the experimental flux measurements. Introduction of branches towards trehalose, glycogen, glycerol and succinate did allow such a steady state. The predictions of this branched model were compared with the empirical behavior. Half of the enzymes matched their predicted flux in vivo within a factor of 2. For the other enzymes it was calculated what deviation between in vivo and in vitro kinetic characteristics could explain the discrepancy between in vitro rate and in vivo flux. %K Enzymes/metabolism %K Glycolysis %K Kinetics %K Models, Biological %K Saccharomyces cerevisiae/*enzymology %+ E.C. Slater Institute, BioCentrum Amsterdam, University of Amsterdam, the Netherlands. %0 Journal Article %A Hull, D. %A Wolstencroft, K. %A Stevens, R. %A Goble, C. %A Pocock, M. R. %A Li, P. %A Oinn, T. %D 2006 %T Taverna: a tool for building and running workflows of services. %J Nucleic Acids Res %V 34 %N Web Server issue %P W729-W732 %M 16845108 %U http://www.ncbi.nlm.nih.gov/pubmed/16845108 %X Taverna is an application that eases the use and integration of the growing number of molecular biology tools and databases available on the web, especially web services. It allows bioinformaticians to construct workflows or pipelines of services to perform a range of different analyses, such as sequence analysis and genome annotation. These high-level workflows can integrate many different resources into a single analysis. Taverna is available freely under the terms of the GNU Lesser General Public License (LGPL) from http://taverna.sourceforge.net/. %K Computational Biology %K *Databases, Genetic %K Genomics %K Internet %K Sequence Analysis %K *Software %K *Systems Integration %K User-Computer Interface %+ School of Computer Science, University of Manchester, M13 9PL, UK. duncan.hull@cs.man.ac.uk %0 Journal Article %A Neves, A. R. %A Ventura, R. %A Mansour, N. %A Shearman, C. %A Gasson, M. J. %A Maycock, C. %A Ramos, A. %A Santos, H. %D 2002 %T Is the glycolytic flux in Lactococcus lactis primarily controlled by the redox charge? Kinetics of NAD(+) and NADH pools determined in vivo by 13C NMR. %J J Biol Chem %V 277 %N 31 %P 28088-28098 %M 12011086 %U http://www.ncbi.nlm.nih.gov/pubmed/12011086 %X The involvement of nicotinamide adenine nucleotides (NAD(+), NADH) in the regulation of glycolysis in Lactococcus lactis was investigated by using (13)C and (31)P NMR to monitor in vivo the kinetics of the pools of NAD(+), NADH, ATP, inorganic phosphate (P(i)), glycolytic intermediates, and end products derived from a pulse of glucose. Nicotinic acid specifically labeled on carbon 5 was synthesized and used in the growth medium as a precursor of pyridine nucleotides to allow for in vivo detection of (13)C-labeled NAD(+) and NADH. The capacity of L. lactis MG1363 to regenerate NAD(+) was manipulated either by turning on NADH oxidase activity or by knocking out the gene encoding lactate dehydrogenase (LDH). An LDH(-) deficient strain was constructed by double crossover. Upon supply of glucose, NAD(+) was constant and maximal (approximately 5 mm) in the parent strain (MG1363) but decreased abruptly in the LDH(-) strain both under aerobic and anaerobic conditions. NADH in MG1363 was always below the detection limit as long as glucose was available. The rate of glucose consumption under anaerobic conditions was 7-fold lower in the LDH(-) strain and NADH reached high levels (2.5 mm), reflecting severe limitation in regenerating NAD(+). However, under aerobic conditions the glycolytic flux was nearly as high as in MG1363 despite the accumulation of NADH up to 1.5 mm. Glyceraldehyde-3-phosphate dehydrogenase was able to support a high flux even in the presence of NADH concentrations much higher than those of the parent strain. We interpret the data as showing that the glycolytic flux in wild type L. lactis is not primarily controlled at the level of glyceraldehyde-3-phosphate dehydrogenase by NADH. The ATP/ADP/P(i) content could play an important role. %K Aerobiosis %K Carbon Isotopes %K Crossing Over, Genetic %K DNA Primers %K Glucose/metabolism %K Glycolysis/*physiology %K Homeostasis %K L-Lactate Dehydrogenase/metabolism %K Lactococcus lactis/genetics/growth & development/*metabolism %K Magnetic Resonance Spectroscopy %K Models, Biological %K Multienzyme Complexes/metabolism %K NAD/*metabolism %K NADH, NADPH Oxidoreductases/metabolism %K Niacin/metabolism %K Oxidation-Reduction %+ Instituto de Tecnologia Quimica e Biologica, Universidade Nova de Lisboa, Oeiras, Portugal. %0 Journal Article %A Cronwright, G. R. %A Rohwer, J. M. %A Prior, B. A. %D 2002 %T Metabolic control analysis of glycerol synthesis in Saccharomyces cerevisiae. %J Appl Environ Microbiol %V 68 %N 9 %P 4448-4456 %M 12200299 %U http://www.ncbi.nlm.nih.gov/pubmed/12200299 %X Glycerol, a major by-product of ethanol fermentation by Saccharomyces cerevisiae, is of significant importance to the wine, beer, and ethanol production industries. To gain a clearer understanding of and to quantify the extent to which parameters of the pathway affect glycerol flux in S. cerevisiae, a kinetic model of the glycerol synthesis pathway has been constructed. Kinetic parameters were collected from published values. Maximal enzyme activities and intracellular effector concentrations were determined experimentally. The model was validated by comparing experimental results on the rate of glycerol production to the rate calculated by the model. Values calculated by the model agreed well with those measured in independent experiments. The model also mimics the changes in the rate of glycerol synthesis at different phases of growth. Metabolic control analysis values calculated by the model indicate that the NAD(+)-dependent glycerol 3-phosphate dehydrogenase-catalyzed reaction has a flux control coefficient (C(J)v1) of approximately 0.85 and exercises the majority of the control of flux through the pathway. Response coefficients of parameter metabolites indicate that flux through the pathway is most responsive to dihydroxyacetone phosphate concentration (R(J)DHAP= 0.48 to 0.69), followed by ATP concentration (R(J)ATP = -0.21 to -0.50). Interestingly, the pathway responds weakly to NADH concentration (R(J)NADH = 0.03 to 0.08). The model indicates that the best strategy to increase flux through the pathway is not to increase enzyme activity, substrate concentration, or coenzyme concentration alone but to increase all of these parameters in conjunction with each other. %K Glycerol/*metabolism %K Kinetics %K Models, Biological %K Saccharomyces cerevisiae/*metabolism %+ Department of Microbiology, Stellenbosch University, Matieland 7602, South Africa. garth.cronwright@tmb.lth.se %0 Journal Article %A Teif, Vladimir B %A Rippe, Karsten %D 2011 %T Nucleosome mediated crosstalk between transcription factors at eukaryotic enhancers %J Phys. Biol. %0 Journal Article %A Courtot, M. %A Juty, N. %A Knupfer, C. %A Waltemath, D. %A Zhukova, A. %A Drager, A. %A Dumontier, M. %A Finney, A. %A Golebiewski, M. %A Hastings, J. %A Hoops, S. %A Keating, S. %A Kell, D. B. %A Kerrien, S. %A Lawson, J. %A Lister, A. %A Lu, J. %A Machne, R. %A Mendes, P. %A Pocock, M. %A Rodriguez, N. %A Villeger, A. %A Wilkinson, D. J. %A Wimalaratne, S. %A Laibe, C. %A Hucka, M. %A Le Novere, N. %D 2011 %T Controlled vocabularies and semantics in systems biology. %J Mol Syst Biol %V 7 %P 543 %M 22027554 %U http://www.ncbi.nlm.nih.gov/pubmed/22027554 %X The use of computational modeling to describe and analyze biological systems is at the heart of systems biology. Model structures, simulation descriptions and numerical results can be encoded in structured formats, but there is an increasing need to provide an additional semantic layer. Semantic information adds meaning to components of structured descriptions to help identify and interpret them unambiguously. Ontologies are one of the tools frequently used for this purpose. We describe here three ontologies created specifically to address the needs of the systems biology community. The Systems Biology Ontology (SBO) provides semantic information about the model components. The Kinetic Simulation Algorithm Ontology (KiSAO) supplies information about existing algorithms available for the simulation of systems biology models, their characterization and interrelationships. The Terminology for the Description of Dynamics (TEDDY) categorizes dynamical features of the simulation results and general systems behavior. The provision of semantic information extends a model's longevity and facilitates its reuse. It provides useful insight into the biology of modeled processes, and may be used to make informed decisions on subsequent simulation experiments. %K Algorithms %K *Computational Biology %K Computer Simulation %K Information Storage and Retrieval %K Models, Biological %K *Semantics %K *Systems Biology %K *Vocabulary, Controlled %+ Terry Fox Laboratory, Vancouver, Canada. %0 Journal Article %A Bonner, H. W. %A Tate, C. A. %A Buffington, C. K. %D 1975 %T Changes in erythrocyte 2,3 diphosphoglycerate in women following short term maximal exercise. %J Eur J Appl Physiol Occup Physiol %V 34 %N 4 %P 227-232 %M 234 %U http://www.ncbi.nlm.nih.gov/pubmed/234 %X 15 untrained women were subjected to a walking treadmill test to determine the influence of maximal exercise upon synthesis of erythrocyte 2,3 DPG. Although there was a 9.8% increase in the 2,3 DPG content following exercise, there was a concomitant 9.4% increase in the hemoglobin level; therefore, when 2,3 DPG is expressed as a ratio to hemoglobin (See Article), there was no significant change as a result of exercise stress. It was suggested that three additive factors produced during strenuous exercise; decreased pH; increased hemoglobin concentration; and increased CO2 production result in by-product inhibition of 2,3 DPG synthesis. It is concluded that 2,3 DPG does not provide a physiologic benefit in the adaptation of the oxygen transport system to exercise. %K Adult %K Carbon Dioxide/blood %K Diphosphoglyceric Acids/biosynthesis/*blood %K Erythrocytes/*metabolism %K Female %K Hemoglobins/metabolism %K Humans %K Hydrogen-Ion Concentration %K Oxygen/blood %K Oxygen Consumption %K *Physical Exertion %0 Journal Article %A Petzold, A. %A Reichwald, K. %A Groth, M. %A Taudien, S. %A Hartmann, N. %A Priebe, S. %A Shagin, D. %A Englert, C. %A Platzer, M. %D 2013 %T The transcript catalogue of the short-lived fish Nothobranchius furzeri provides insights into age-dependent changes of mRNA levels. %J BMC Genomics %V 14 %P 185 %M 23496936 %U http://www.ncbi.nlm.nih.gov/pubmed/23496936 %X BACKGROUND: The African annual fish Nothobranchius furzeri has over recent years been established as a model species for ageing-related studies. This is mainly based on its exceptionally short lifespan and the presence of typical characteristics of vertebrate ageing. To substantiate its role as an alternative vertebrate ageing model, a transcript catalogue is needed, which can serve e.g. as basis for identifying ageing-related genes. RESULTS: To build the N. furzeri transcript catalogue, thirteen cDNA libraries were sequenced using Sanger, 454/Roche and Solexa/Illumina technologies yielding about 39 Gb. In total, 19,875 protein-coding genes were identified and annotated. Of these, 71% are represented by at least one transcript contig with a complete coding sequence. Further, transcript levels of young and old fish of the strains GRZ and MZM-0403, which differ in lifespan by twofold, were studied by RNA-seq. In skin and brain, 85 differentially expressed genes were detected; these have a role in cell cycle control and proliferation, inflammation and tissue maintenance. An RNA-seq experiment for zebrafish skin confirmed the ageing-related relevance of the findings in N. furzeri. Notably, analyses of transcript levels between zebrafish and N. furzeri but also between N. furzeri strains differed largely, suggesting that ageing is accelerated in the short-lived N. furzeri strain GRZ compared to the longer-lived strain MZM-0403. CONCLUSIONS: We provide a comprehensive, annotated N. furzeri transcript catalogue and a first transcriptome-wide insight into N. furzeri ageing. This data will serve as a basis for future functional studies of ageing-related genes. %K Aging/*genetics %K Animals %K Cyprinodontiformes/*genetics/physiology %K Gene Expression Profiling %K Gene Expression Regulation, Developmental %K Gene Library %K High-Throughput Nucleotide Sequencing %K Molecular Sequence Annotation %K RNA, Messenger/*genetics/physiology %K Zebrafish/genetics/growth & development %+ Genome Analysis, Leibniz Institute for Age Research - Fritz Lipmann Institute, Beutenbergstr. 11, Jena 07745, Germany. andpet@fli-leibniz.de %0 Journal Article %A Allen, E. K. %A Koeppel, A. F. %A Hendley, J. O. %A Turner, S. D. %A Winther, B. %A Sale, M. M. %D 2014 %T Characterization of the nasopharyngeal microbiota in health and during rhinovirus challenge. %J Microbiome %V 2 %P 22 %M 25028608 %U http://www.ncbi.nlm.nih.gov/pubmed/25028608 %X BACKGROUND: The bacterial communities of the nasopharynx play an important role in upper respiratory tract infections (URTIs). Our study represents the first survey of the nasopharynx during a known, controlled viral challenge. We aimed to gain a better understanding of the composition and dynamics of the nasopharyngeal microbiome during viral infection. METHODS: Rhinovirus illnesses were induced by self-inoculation using the finger to nose or eye natural transmission route in ten otherwise healthy young adults. Nasal lavage fluid samples (NLF) samples were collected at specific time points before, during, and following experimental rhinovirus inoculation. Bacterial DNA from each sample (N = 97 from 10 subjects) was subjected to 16S rRNA sequencing by amplifying the V1-V2 hypervariable region followed by sequencing using the 454-FLX platform. RESULTS: This survey of the nasopharyngeal microbiota revealed a highly complex microbial ecosystem. Taxonomic composition varied widely between subjects and between time points of the same subject. We also observed significantly higher diversity in not infected individuals compared to infected individuals. Two genera - Neisseria and Propionibacterium - differed significantly between infected and not infected individuals. Certain phyla, including Firmicutes, Actinobacteria, and Proteobacteria, were detected in all samples. CONCLUSIONS: Our results reveal the complex and diverse nature of the nasopharyngeal microbiota in both healthy and viral-challenged adults. Although some phyla were common to all samples, differences in levels of diversity and selected phyla were detected between infected and uninfected participants. Deeper, species-level metagenomic sequencing in a larger sample is warranted. %+ Center for Public Health Genomics, University of Virginia, PO Box 800717, Charlottesville, USA ; Department of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, USA. Bioinformatics Core Facility, University of Virginia, Charlottesville, USA. Department of Pediatrics, University of Virginia, Charlottesville, USA. Bioinformatics Core Facility, University of Virginia, Charlottesville, USA. Department of Otolaryngology, University of Virginia, Charlottesville, USA. Center for Public Health Genomics, University of Virginia, PO Box 800717, Charlottesville, USA ; Department of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, USA ; Department of Medicine, University of Virginia, Charlottesville, USA. %0 Journal Article %A Abeyruwan, Saminda %A Vempati, Uma D %A Küçük-McGinty, Hande %A Visser, Ubbo %A Koleti, Amar %A Mir, Ahsan %A Sakurai, Kunie %A Chung, Caty %A Bittker, Joshua A %A Clemons, Paul A %A Brudz, Steve %A Siripala, Anosha %A Morales, Arturo J %A Romacker, Martin %A Twomey, David %A Bureeva, Svetlana %A Lemmon, Vance %A Schürer, Stephan C %D 2014 %T Evolving BioAssay Ontology (BAO): modularization, integration and applications %J J Biomed Sem %0 Journal Article %A Kouril, T. %A Esser, D. %A Kort, J. %A Westerhoff, H. V. %A Siebers, B. %A Snoep, J. L. %D 2013 %T Intermediate instability at high temperature leads to low pathway efficiency for an in vitro reconstituted system of gluconeogenesis in Sulfolobus solfataricus. %J FEBS J %V 280 %N 18 %P 4666-4680 %M 23865479 %U http://www.ncbi.nlm.nih.gov/pubmed/23865479 %X Four enzymes of the gluconeogenic pathway in Sulfolobus solfataricus were purified and kinetically characterized. The enzymes were reconstituted in vitro to quantify the contribution of temperature instability of the pathway intermediates to carbon loss from the system. The reconstituted system, consisting of phosphoglycerate kinase, glyceraldehyde 3-phosphate dehydrogenase, triose phosphate isomerase and the fructose 1,6-bisphosphate aldolase/phosphatase, maintained a constant consumption rate of 3-phosphoglycerate and production of fructose 6-phosphate over a 1-h period. Cofactors ATP and NADPH were regenerated via pyruvate kinase and glucose dehydrogenase. A mathematical model was constructed on the basis of the kinetics of the purified enzymes and the measured half-life times of the pathway intermediates. The model quantitatively predicted the system fluxes and metabolite concentrations. Relative enzyme concentrations were chosen such that half the carbon in the system was lost due to degradation of the thermolabile intermediates dihydroxyacetone phosphate, glyceraldehyde 3-phosphate and 1,3-bisphosphoglycerate, indicating that intermediate instability at high temperature can significantly affect pathway efficiency. %K Archaeal Proteins/genetics/*metabolism %K Dihydroxyacetone Phosphate/metabolism %K Diphosphoglyceric Acids/metabolism %K Enzyme Stability %K Escherichia coli/genetics/metabolism %K Fructose-Bisphosphate Aldolase/genetics/*metabolism %K Fructosephosphates/biosynthesis %K Gluconeogenesis/genetics %K Glyceraldehyde 3-Phosphate/metabolism %K Glyceraldehyde-3-Phosphate Dehydrogenases/genetics/*metabolism %K Glyceric Acids/metabolism %K Half-Life %K Hot Temperature %K Kinetics %K *Models, Statistical %K Phosphoglycerate Kinase/genetics/*metabolism %K Recombinant Proteins/genetics/metabolism %K Sulfolobus solfataricus/chemistry/*enzymology/genetics %K Thermodynamics %K Triose-Phosphate Isomerase/genetics/*metabolism %+ Molecular Enzyme Technology and Biochemistry, Biofilm Centre, Faculty of Chemistry, University of Duisburg-Essen, Germany. %0 Journal Article %A Wilkinson, M. D. %A Dumontier, M. %A Aalbersberg, I. J. %A Appleton, G. %A Axton, M. %A Baak, A. %A Blomberg, N. %A Boiten, J. W. %A da Silva Santos, L. B. %A Bourne, P. E. %A Bouwman, J. %A Brookes, A. J. %A Clark, T. %A Crosas, M. %A Dillo, I. %A Dumon, O. %A Edmunds, S. %A Evelo, C. T. %A Finkers, R. %A Gonzalez-Beltran, A. %A Gray, A. J. %A Groth, P. %A Goble, C. %A Grethe, J. S. %A Heringa, J. %A 't Hoen, P. A. %A Hooft, R. %A Kuhn, T. %A Kok, R. %A Kok, J. %A Lusher, S. J. %A Martone, M. E. %A Mons, A. %A Packer, A. L. %A Persson, B. %A Rocca-Serra, P. %A Roos, M. %A van Schaik, R. %A Sansone, S. A. %A Schultes, E. %A Sengstag, T. %A Slater, T. %A Strawn, G. %A Swertz, M. A. %A Thompson, M. %A van der Lei, J. %A van Mulligen, E. %A Velterop, J. %A Waagmeester, A. %A Wittenburg, P. %A Wolstencroft, K. %A Zhao, J. %A Mons, B. %D 2016 %T The FAIR Guiding Principles for scientific data management and stewardship. %J Sci Data %V 3 %P 160018 %M 26978244 %U http://www.ncbi.nlm.nih.gov/pubmed/26978244 %X There is an urgent need to improve the infrastructure supporting the reuse of scholarly data. A diverse set of stakeholders-representing academia, industry, funding agencies, and scholarly publishers-have come together to design and jointly endorse a concise and measureable set of principles that we refer to as the FAIR Data Principles. The intent is that these may act as a guideline for those wishing to enhance the reusability of their data holdings. Distinct from peer initiatives that focus on the human scholar, the FAIR Principles put specific emphasis on enhancing the ability of machines to automatically find and use the data, in addition to supporting its reuse by individuals. This Comment is the first formal publication of the FAIR Principles, and includes the rationale behind them, and some exemplar implementations in the community. %K *Data Collection %K *Data Curation %K Database Management Systems %K Guidelines as Topic %K Reproducibility of Results %K *Research Design %+ Center for Plant Biotechnology and Genomics, Universidad Politecnica de Madrid, Madrid 28223, Spain. Stanford University, Stanford 94305-5411, USA. Nature Genetics, New York 10004-1562, USA. Euretos and Phortos Consultants, Rotterdam 2741 CA, The Netherlands. ELIXIR, Wellcome Genome Campus, Hinxton CB10 1SA, UK. Lygature, Eindhoven 5656 AG, The Netherlands. Vrije Universiteit Amsterdam, Dutch Techcenter for Life Sciences, Amsterdam 1081 HV, The Netherlands. Office of the Director, National Institutes of Health, Rockville 20892, USA. TNO, Zeist 3700 AJ, The Netherlands. Department of Genetics, University of Leicester, Leicester LE1 7RH, UK. Harvard Medical School, Boston, Massachusetts MA 02115, USA. Harvard University, Cambridge, Massachusetts MA 02138, USA. Data Archiving and Networked Services (DANS), The Hague 2593 HW, The Netherlands. GigaScience, Beijing Genomics Institute, Shenzhen 518083, China. Department of Bioinformatics, Maastricht University, Maastricht 6200 MD, The Netherlands. Wageningen UR Plant Breeding, Wageningen 6708 PB, The Netherlands. Oxford e-Research Center, University of Oxford, Oxford OX1 3QG, UK. Heriot-Watt University, Edinburgh EH14 4AS, UK. School of Computer Science, University of Manchester, Manchester M13 9PL, UK. Center for Research in Biological Systems, School of Medicine, University of California San Diego, La Jolla, California 92093-0446, USA. Dutch Techcenter for the Life Sciences, Utrecht 3501 DE, The Netherlands. Department of Human Genetics, Leiden University Medical Center, Dutch Techcenter for the Life Sciences, Leiden 2300 RC, The Netherlands. Dutch TechCenter for Life Sciences and ELIXIR-NL, Utrecht 3501 DE, The Netherlands. VU University Amsterdam, Amsterdam 1081 HV, The Netherlands. Dutch Techcenter for the Life Sciences, Utrecht 3501 DE, The Netherlands. Leiden Center of Data Science, Leiden University, Leiden 2300 RA, The Netherlands. Netherlands eScience Center, Amsterdam 1098 XG, The Netherlands. National Center for Microscopy and Imaging Research, UCSD, San Diego 92103, USA. Phortos Consultants, San Diego 92011, USA. SciELO/FAPESP Program, UNIFESP Foundation, Sao Paulo 05468-901, Brazil. Bioinformatics Infrastructure for Life Sciences (BILS), Science for Life Laboratory, Dept of Cell and Molecular Biology, Uppsala University, S-751 24, Uppsala, Sweden. Oxford e-Research Center, University of Oxford, Oxford OX1 3QG, UK. Leiden University Medical Center, Leiden 2333 ZA, The Netherlands. Bayer CropScience, Gent Area 1831, Belgium. Oxford e-Research Center, University of Oxford, Oxford OX1 3QG, UK. Leiden Institute for Advanced Computer Science, Leiden University Medical Center, Leiden 2300 RA, The Netherlands. Swiss Institute of Bioinformatics and University of Basel, Basel 4056, Switzerland. Cray, Inc., Seattle 98164, USA. University Medical Center Groningen (UMCG), University of Groningen, Groningen 9713 GZ, The Netherlands. Leiden University Medical Center, Leiden 2333 ZA, The Netherlands. Erasmus MC, Rotterdam 3015 CE, The Netherlands. Erasmus MC, Rotterdam 3015 CE, The Netherlands. Independent Open Access and Open Science Advocate, Guildford GU1 3PW, UK. Micelio, Antwerp 2180, Belgium. Max Planck Compute and Data Facility, MPS, Garching 85748, Germany. Leiden Institute of Advanced Computer Science, Leiden University, Leiden 2333 CA, The Netherlands. Department of Computer Science, Oxford University, Oxford OX1 3QD, UK. Leiden University Medical Center, Leiden and Dutch TechCenter for Life Sciences, Utrecht 2333 ZA, The Netherlands. Netherlands eScience Center, Amsterdam 1098 XG, The Netherlands. Erasmus MC, Rotterdam 3015 CE, The Netherlands. %0 Journal Article %A Tyson, J. J. %D 1991 %T Modeling the cell division cycle: cdc2 and cyclin interactions. %J Proc Natl Acad Sci U S A %V 88 %N 16 %P 7328-7332 %M 1831270 %U http://www.ncbi.nlm.nih.gov/pubmed/1831270 %X The proteins cdc2 and cyclin form a heterodimer (maturation promoting factor) that controls the major events of the cell cycle. A mathematical model for the interactions of cdc2 and cyclin is constructed. Simulation and analysis of the model show that the control system can operate in three modes: as a steady state with high maturation promoting factor activity, as a spontaneous oscillator, or as an excitable switch. We associate the steady state with metaphase arrest in unfertilized eggs, the spontaneous oscillations with rapid division cycles in early embryos, and the excitable switch with growth-controlled division cycles typical of nonembryonic cells. %K Animals %K CDC2 Protein Kinase/*metabolism %K *Cell Division %K Cyclins/*metabolism %K Kinetics %K Mathematics %K Maturation-Promoting Factor/physiology %K Mitosis %K *Models, Biological %+ Department of Biology, Virginia Polytechnic Institute and State University, Blacksburg 24061. %0 Journal Article %A Meineke, F. A. %A Lobe, M. %A Staubert, S. %D 2018 %T Introducing Technical Aspects of Research Data Management in the Leipzig Health Atlas. %J Stud Health Technol Inform %V 247 %P 426-430 %M 29677996 %U http://www.ncbi.nlm.nih.gov/pubmed/29677996 %X Medical research is an active field in which a wide range of information is collected, collated, combined and analyzed. Essential results are reported in publications, but it is often problematic to have the data (raw and processed), algorithms and tools associated with the publication available. The Leipzig Health Atlas (LHA) project has therefore set itself the goal of providing a repository for this purpose and enabling controlled access to it via a web-based portal. A data sharing concept in accordance to FAIR and OAIS is the basis for the processing and provision of data in the LHA. An IT architecture has been designed for this purpose. The paper presents essential aspects of the data sharing concept, the IT architecture and the methods used. %K *Algorithms %K Humans %K Research %K *Statistics as Topic %+ Institute for Medical Informatics, Statistics and Epidemiology (IMISE), Universitat Leipzig, Germany. Institute for Medical Informatics, Statistics and Epidemiology (IMISE), Universitat Leipzig, Germany. Institute for Medical Informatics, Statistics and Epidemiology (IMISE), Universitat Leipzig, Germany. %0 Journal Article %A Loeffler-Wirth, H. %A Vogel, M. %A Kirsten, T. %A Glock, F. %A Poulain, T. %A Korner, A. %A Loeffler, M. %A Kiess, W. %A Binder, H. %D 2018 %T Longitudinal anthropometry of children and adolescents using 3D-body scanning. %J PLoS One %V 13 %N 9 %P e0203628 %M 30212520 %U http://www.ncbi.nlm.nih.gov/pubmed/30212520 %X 3D-body scanning anthropometry is a suitable method for characterization of physiological development of children and adolescents, and for understanding onset and progression of disorders like overweight and obesity. Here we present a novel body typing approach to describe and to interpret longitudinal 3D-body scanning data of more than 800 children and adolescents measured in up to four follow-ups in intervals of 1 year, referring to an age range between 6 and 18 years. We analyzed transitions between body types assigned to lower-, normal- and overweight participants upon development of children and adolescents. We found a virtually parallel development of the body types with only a few transitions between them. Body types of children and adolescents tend to conserve their weight category. 3D body scanning anthropometry in combination with body typing constitutes a novel option to investigate onset and progression of obesity in children. %K Adolescent %K Anthropometry/*methods %K Child %K Female %K Humans %K Male %K Obesity/*pathology/physiopathology %K Overweight/pathology/physiopathology %K Somatotypes %+ Interdisciplinary Centre for Bioinformatics, Leipzig University, Leipzig, Germany. LIFE, Leipzig Research Center for Civilization Diseases; Leipzig University, Leipzig, Germany. LIFE, Leipzig Research Center for Civilization Diseases; Leipzig University, Leipzig, Germany. LIFE, Leipzig Research Center for Civilization Diseases; Leipzig University, Leipzig, Germany. LIFE, Leipzig Research Center for Civilization Diseases; Leipzig University, Leipzig, Germany. Hospital for Children and Adolescents, Centre for Pediatric Research; Leipzig University, Leipzig, Germany. LIFE, Leipzig Research Center for Civilization Diseases; Leipzig University, Leipzig, Germany. LIFE, Leipzig Research Center for Civilization Diseases; Leipzig University, Leipzig, Germany. Hospital for Children and Adolescents, Centre for Pediatric Research; Leipzig University, Leipzig, Germany. Interdisciplinary Centre for Bioinformatics, Leipzig University, Leipzig, Germany. LIFE, Leipzig Research Center for Civilization Diseases; Leipzig University, Leipzig, Germany. Institute for Medical Informatics, Statistics and Epidemiology, Leipzig University, Leipzig, Germany. LIFE, Leipzig Research Center for Civilization Diseases; Leipzig University, Leipzig, Germany. Hospital for Children and Adolescents, Centre for Pediatric Research; Leipzig University, Leipzig, Germany. Interdisciplinary Centre for Bioinformatics, Leipzig University, Leipzig, Germany. LIFE, Leipzig Research Center for Civilization Diseases; Leipzig University, Leipzig, Germany. %0 Journal Article %A Van Bel, Michiel %A Diels, Tim %A Vancaester, Emmelien %A Kreft, Lukasz %A Botzki, Alexander %A Van de Peer, Yves %A Coppens, Frederik %A Vandepoele, Klaas %D 2018 %T PLAZA 4.0: an integrative resource for functional, evolutionary and comparative plant genomics %J Nucleic Acids Research