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Santos-Moreno J, Tasiudi E, Kusumawardhani H, Stelling J, Schaerli Y. Robustness and innovation in synthetic genotype networks. Nat Commun 2023; 14:2454. [PMID: 37117168 PMCID: PMC10147661 DOI: 10.1038/s41467-023-38033-3] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2022] [Accepted: 04/13/2023] [Indexed: 04/30/2023] Open
Abstract
Genotype networks are sets of genotypes connected by small mutational changes that share the same phenotype. They facilitate evolutionary innovation by enabling the exploration of different neighborhoods in genotype space. Genotype networks, first suggested by theoretical models, have been empirically confirmed for proteins and RNAs. Comparative studies also support their existence for gene regulatory networks (GRNs), but direct experimental evidence is lacking. Here, we report the construction of three interconnected genotype networks of synthetic GRNs producing three distinct phenotypes in Escherichia coli. Our synthetic GRNs contain three nodes regulating each other by CRISPR interference and governing the expression of fluorescent reporters. The genotype networks, composed of over twenty different synthetic GRNs, provide robustness in face of mutations while enabling transitions to innovative phenotypes. Through realistic mathematical modeling, we quantify robustness and evolvability for the complete genotype-phenotype map and link these features mechanistically to GRN motifs. Our work thereby exemplifies how GRN evolution along genotype networks might be driving evolutionary innovation.
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Santos-Moreno J, Tasiudi E, Stelling J, Schaerli Y. Author Correction: Multistable and dynamic CRISPRi-based synthetic circuits. Nat Commun 2021; 12:3119. [PMID: 34011942 PMCID: PMC8134505 DOI: 10.1038/s41467-021-23622-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022] Open
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Yordanov P, Stelling J, Otero-Muras I. BioSwitch: a tool for the detection of bistability and multi-steady state behaviour in signalling and gene regulatory networks. Bioinformatics 2020; 36:1640-1641. [PMID: 31609384 DOI: 10.1093/bioinformatics/btz746] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2019] [Revised: 08/28/2019] [Accepted: 10/10/2019] [Indexed: 11/14/2022] Open
Abstract
MOTIVATION Multi-steady state behaviour, and in particular multi-stability, provides biological systems with the capacity to take reliable decisions (such as cell fate determination). A problem arising frequently in systems biology is to elucidate whether a signal transduction mechanism or a gene regulatory network has the capacity for multi-steady state behaviour, and consequently for a switch-like response to stimuli. Bifurcation diagrams are a powerful instrument in non-linear analysis to study the qualitative and quantitative behaviour of equilibria including bifurcation into different equilibrium branches and bistability. However, in the context of signalling pathways, the inherent large parametric uncertainty hampers the (direct) use of standard bifurcation tools. RESULTS We present BioSwitch, a toolbox to detect multi-steady state behaviour in signalling pathways and gene regulatory networks. The tool combines results from chemical reaction network theory with global optimization to efficiently detect whether a signalling pathway has the capacity to undergo a saddle node bifurcation, and in case of multi-stationarity, provides the exact coordinates of the bifurcation where to start a numerical continuation analysis with standard bifurcation tools, leading to two different branches of equilibria. Bistability detection in the G1/S transition pathway of Saccharomyces cerevisiae is included as an illustrative example. AVAILABILITY AND IMPLEMENTATION BioSwitch runs under the popular MATLAB computational environment, and is available at https://sites.google.com/view/bioswitch.
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Keating SM, Waltemath D, König M, Zhang F, Dräger A, Chaouiya C, Bergmann FT, Finney A, Gillespie CS, Helikar T, Hoops S, Malik‐Sheriff RS, Moodie SL, Moraru II, Myers CJ, Naldi A, Olivier BG, Sahle S, Schaff JC, Smith LP, Swat MJ, Thieffry D, Watanabe L, Wilkinson DJ, Blinov ML, Begley K, Faeder JR, Gómez HF, Hamm TM, Inagaki Y, Liebermeister W, Lister AL, Lucio D, Mjolsness E, Proctor CJ, Raman K, Rodriguez N, Shaffer CA, Shapiro BE, Stelling J, Swainston N, Tanimura N, Wagner J, Meier‐Schellersheim M, Sauro HM, Palsson B, Bolouri H, Kitano H, Funahashi A, Hermjakob H, Doyle JC, Hucka M. SBML Level 3: an extensible format for the exchange and reuse of biological models. Mol Syst Biol 2020; 16:e9110. [PMID: 32845085 PMCID: PMC8411907 DOI: 10.15252/msb.20199110] [Citation(s) in RCA: 115] [Impact Index Per Article: 28.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2019] [Revised: 06/24/2020] [Accepted: 07/09/2020] [Indexed: 12/25/2022] Open
Abstract
Systems biology has experienced dramatic growth in the number, size, and complexity of computational models. To reproduce simulation results and reuse models, researchers must exchange unambiguous model descriptions. We review the latest edition of the Systems Biology Markup Language (SBML), a format designed for this purpose. A community of modelers and software authors developed SBML Level 3 over the past decade. Its modular form consists of a core suited to representing reaction-based models and packages that extend the core with features suited to other model types including constraint-based models, reaction-diffusion models, logical network models, and rule-based models. The format leverages two decades of SBML and a rich software ecosystem that transformed how systems biologists build and interact with models. More recently, the rise of multiscale models of whole cells and organs, and new data sources such as single-cell measurements and live imaging, has precipitated new ways of integrating data with models. We provide our perspectives on the challenges presented by these developments and how SBML Level 3 provides the foundation needed to support this evolution.
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Rubin L, Pastore L, Subramony S, Lobel M, Stelling J. Navigating preimplantation genetic testing decisions in the age of social media: a qualitative study. Fertil Steril 2018. [DOI: 10.1016/j.fertnstert.2018.07.431] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
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Jackman J, Chatzicharalampous C, Saketos M, Stelling J, Sung L, Robertazzi R, Bray M. The increased cost of success of IVF in obese women. Fertil Steril 2018. [DOI: 10.1016/j.fertnstert.2018.07.364] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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Genoff Garzon MC, Rubin LR, Lobel M, Stelling J, Pastore LM. Review of patient decision-making factors and attitudes regarding preimplantation genetic diagnosis. Clin Genet 2018; 94:22-42. [PMID: 29120067 DOI: 10.1111/cge.13174] [Citation(s) in RCA: 35] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2017] [Revised: 10/31/2017] [Accepted: 11/01/2017] [Indexed: 12/22/2022]
Abstract
The increasing technical complexity and evolving options for repro-genetic testing have direct implications for information processing and decision making, yet the research among patients considering preimplantation genetic diagnosis (PGD) is narrowly focused. This review synthesizes the literature regarding patient PGD decision-making factors, and illuminates gaps for future research and clinical translation. Twenty-five articles met the inclusion criteria for evaluating experiences and attitudes of patients directly involved in PGD as an intervention or considering using PGD. Thirteen reports were focused exclusively on a specific disease or condition. Five themes emerged: (1) patients motivated by prospects of a healthy, genetic-variant-free child, (2) PGD requires a commitment of time, money, energy and emotions, (3) patients concerned about logistics and ethics of discarding embryos, (4) some patients feel sense of responsibility to use available technologies, and (5) PGD decisions are complex for individuals and couples. Patient research on PGD decision-making processes has very infrequently used validated instruments, and the data collected through both quantitative and qualitative designs have been inconsistent. Future research for improving clinical counseling is needed to fill many gaps remaining in the literature regarding this decision-making process, and suggestions are offered.
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Hass H, Masson K, Wohlgemuth S, Paragas V, Allen JE, Sevecka M, Pace E, Timmer J, Stelling J, MacBeath G, Schoeberl B, Raue A. Predicting ligand-dependent tumors from multi-dimensional signaling features. NPJ Syst Biol Appl 2017; 3:27. [PMID: 28944080 PMCID: PMC5607260 DOI: 10.1038/s41540-017-0030-3] [Citation(s) in RCA: 30] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2017] [Revised: 08/23/2017] [Accepted: 08/28/2017] [Indexed: 12/11/2022] Open
Abstract
Targeted therapies have shown significant patient benefit in about 5-10% of solid tumors that are addicted to a single oncogene. Here, we explore the idea of ligand addiction as a driver of tumor growth. High ligand levels in tumors have been shown to be associated with impaired patient survival, but targeted therapies have not yet shown great benefit in unselected patient populations. Using an approach of applying Bagged Decision Trees (BDT) to high-dimensional signaling features derived from a computational model, we can predict ligand dependent proliferation across a set of 58 cell lines. This mechanistic, multi-pathway model that features receptor heterodimerization, was trained on seven cancer cell lines and can predict signaling across two independent cell lines by adjusting only the receptor expression levels for each cell line. Interestingly, for patient samples the predicted tumor growth response correlates with high growth factor expression in the tumor microenvironment, which argues for a co-evolution of both factors in vivo.
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Chatzicharalampous C, Saketos M, Sung L, Stelling J, Jackman J, Bray M. Vitamin D levels and IVF outcomes in women of different ethnic groups. Fertil Steril 2017. [DOI: 10.1016/j.fertnstert.2017.07.361] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
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10
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Otero-Muras I, Yordanov P, Stelling J. Chemical Reaction Network Theory elucidates sources of multistability in interferon signaling. PLoS Comput Biol 2017; 13:e1005454. [PMID: 28369103 PMCID: PMC5400276 DOI: 10.1371/journal.pcbi.1005454] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2015] [Revised: 04/21/2017] [Accepted: 03/13/2017] [Indexed: 11/29/2022] Open
Abstract
Bistability has important implications in signaling pathways, since it indicates a potential cell decision between alternative outcomes. We present two approaches developed in the framework of the Chemical Reaction Network Theory for easy and efficient search of multiple steady state behavior in signaling networks (both with and without mass conservation), and apply them to search for sources of bistability at different levels of the interferon signaling pathway. Different type I interferon subtypes and/or doses are known to elicit differential bioactivities (ranging from antiviral, antiproliferative to immunomodulatory activities). How different signaling outcomes can be generated through the same receptor and activating the same JAK/STAT pathway is still an open question. Here, we detect bistability at the level of early STAT signaling, showing how two different cell outcomes are achieved under or above a threshold in ligand dose or ligand-receptor affinity. This finding could contribute to explain the differential signaling (antiviral vs apoptotic) depending on interferon dose and subtype (α vs β) observed in type I interferons.
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Xie M, Ye H, Wang H, Charpin-El Hamri G, Lormeau C, Saxena P, Stelling J, Fussenegger M. -cell-mimetic designer cells provide closed-loop glycemic control. Science 2016; 354:1296-1301. [DOI: 10.1126/science.aaf4006] [Citation(s) in RCA: 140] [Impact Index Per Article: 17.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2016] [Accepted: 11/10/2016] [Indexed: 12/12/2022]
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12
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Chatzicharalampous C, Bray M, Jackman J, Saketos M, Sung L, Stelling J. Should minority women have only frozen-thawed embryos transfers? Fertil Steril 2016. [DOI: 10.1016/j.fertnstert.2016.07.943] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
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13
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van Heck RGA, Ganter M, Martins dos Santos VAP, Stelling J. Efficient Reconstruction of Predictive Consensus Metabolic Network Models. PLoS Comput Biol 2016; 12:e1005085. [PMID: 27563720 PMCID: PMC5001716 DOI: 10.1371/journal.pcbi.1005085] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2016] [Accepted: 07/29/2016] [Indexed: 01/08/2023] Open
Abstract
Understanding cellular function requires accurate, comprehensive representations of metabolism. Genome-scale, constraint-based metabolic models (GSMs) provide such representations, but their usability is often hampered by inconsistencies at various levels, in particular for concurrent models. COMMGEN, our tool for COnsensus Metabolic Model GENeration, automatically identifies inconsistencies between concurrent models and semi-automatically resolves them, thereby contributing to consolidate knowledge of metabolic function. Tests of COMMGEN for four organisms showed that automatically generated consensus models were predictive and that they substantially increased coherence of knowledge representation. COMMGEN ought to be particularly useful for complex scenarios in which manual curation does not scale, such as for eukaryotic organisms, microbial communities, and host-pathogen interactions.
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Armenti E, Jordan A, Goldberg-Strassler D, Cabey R, Barrionuevo M, Kiltz R, Racowsky C, Stelling J, Kenigsberg D, Vitiello D, Munne S. PGD via ACGH for translocations: a review of cycle outcomes. Fertil Steril 2015. [DOI: 10.1016/j.fertnstert.2015.07.229] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
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16
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Chatzicharalampous C, Stelling J, Jenkins J, Saketos M, Sung L, Bray M. Should embryo transfer number be upgraded in ethnic minority groups? Fertil Steril 2015. [DOI: 10.1016/j.fertnstert.2015.07.690] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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Egli A, Humar A, Widmer LA, Lisboa LF, Santer DM, Mueller T, Stelling J, Baluch A, O'Shea D, Houghton M, Kumar D. Effect of Immunosuppression on T-Helper 2 and B-Cell Responses to Influenza Vaccination. J Infect Dis 2015; 212:137-46. [DOI: 10.1093/infdis/jiv015] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2014] [Accepted: 12/23/2014] [Indexed: 12/23/2022] Open
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Ottoz DSM, Rudolf F, Stelling J. Inducible, tightly regulated and growth condition-independent transcription factor in Saccharomyces cerevisiae. Nucleic Acids Res 2014; 42:e130. [PMID: 25034689 PMCID: PMC4176152 DOI: 10.1093/nar/gku616] [Citation(s) in RCA: 92] [Impact Index Per Article: 9.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
The precise control of gene expression is essential in basic biological research as well as in biotechnological applications. Most regulated systems available in yeast enable only the overexpression of the target gene, excluding the possibility of intermediate or weak expression. Moreover, these systems are frequently toxic or depend on growth conditions. We constructed a heterologous transcription factor that overcomes these limitations. Our system is a fusion of the bacterial LexA DNA-binding protein, the human estrogen receptor (ER) and an activation domain (AD). The activity of this chimera, called LexA-ER-AD, is tightly regulated by the hormone β-estradiol. The selection of the AD proved to be crucial to avoid toxic effects and to define the range of activity that can be precisely tuned with β-estradiol. As our system is based on a heterologous DNA-binding domain, induction in different metabolic contexts is possible. Additionally, by controlling the number of LexA-binding sites in the target promoter, one can scale the expression levels up or down. Overall, our LexA-ER-AD system is a valuable tool to precisely control gene expression in different experimental contexts without toxic side effects.
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Dimopoulos S, Mayer CE, Rudolf F, Stelling J. Accurate cell segmentation in microscopy images using membrane patterns. Bioinformatics 2014; 30:2644-51. [DOI: 10.1093/bioinformatics/btu302] [Citation(s) in RCA: 103] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
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20
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Sunnåker M, Zamora-Sillero E, López García de Lomana A, Rudroff F, Sauer U, Stelling J, Wagner A. Topological augmentation to infer hidden processes in biological systems. Bioinformatics 2014; 30:221-7. [PMID: 24297519 PMCID: PMC3892687 DOI: 10.1093/bioinformatics/btt638] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2013] [Revised: 10/28/2013] [Accepted: 10/31/2013] [Indexed: 11/12/2022] Open
Abstract
MOTIVATION A common problem in understanding a biochemical system is to infer its correct structure or topology. This topology consists of all relevant state variables-usually molecules and their interactions. Here we present a method called topological augmentation to infer this structure in a statistically rigorous and systematic way from prior knowledge and experimental data. RESULTS Topological augmentation starts from a simple model that is unable to explain the experimental data and augments its topology by adding new terms that capture the experimental behavior. This process is guided by representing the uncertainty in the model topology through stochastic differential equations whose trajectories contain information about missing model parts. We first apply this semiautomatic procedure to a pharmacokinetic model. This example illustrates that a global sampling of the parameter space is critical for inferring a correct model structure. We also use our method to improve our understanding of glutamine transport in yeast. This analysis shows that transport dynamics is determined by glutamine permeases with two different kinds of kinetics. Topological augmentation can not only be applied to biochemical systems, but also to any system that can be described by ordinary differential equations. AVAILABILITY AND IMPLEMENTATION Matlab code and examples are available at: http://www.csb.ethz.ch/tools/index
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Widmer LA, Stelling J, Doyle FJ. Note: Parameter-independent bounding of the stochastic Michaelis-Menten steady-state intrinsic noise variance. J Chem Phys 2013; 139:166102. [DOI: 10.1063/1.4827496] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
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Patel D, John N, Chatzicharalampous C, Virji N, Stelling J, Bray M. IUI treatment beyond 3 cycles is not at excercise in futility, especially in older women. Fertil Steril 2013. [DOI: 10.1016/j.fertnstert.2013.07.431] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
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John N, Persad M, John T, Jenkins J, Bray M, Stelling J. Is there an association between body mass index and pregnancy outcomes in frozen-thawed embryo transfer cycles? Fertil Steril 2013. [DOI: 10.1016/j.fertnstert.2013.07.883] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
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Chatzicharalampous C, Patel D, Jenkins J, Virji N, Stelling J, Bray M. Should we continue grading ICM or TE? Fertil Steril 2013. [DOI: 10.1016/j.fertnstert.2013.07.320] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
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Sunnaker M, Zamora-Sillero E, Dechant R, Ludwig C, Busetto AG, Wagner A, Stelling J. Automatic Generation of Predictive Dynamic Models Reveals Nuclear Phosphorylation as the Key Msn2 Control Mechanism. Sci Signal 2013; 6:ra41. [DOI: 10.1126/scisignal.2003621] [Citation(s) in RCA: 41] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
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Ganter M, Bernard T, Moretti S, Stelling J, Pagni M. MetaNetX.org: a website and repository for accessing, analysing and manipulating metabolic networks. Bioinformatics 2013; 29:815-6. [PMID: 23357920 PMCID: PMC3597148 DOI: 10.1093/bioinformatics/btt036] [Citation(s) in RCA: 70] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/15/2023] Open
Abstract
MetaNetX.org is a website for accessing, analysing and manipulating genome-scale metabolic networks (GSMs) as well as biochemical pathways. It consistently integrates data from various public resources and makes the data accessible in a standardized format using a common namespace. Currently, it provides access to hundreds of GSMs and pathways that can be interactively compared (two or more), analysed (e.g. detection of dead-end metabolites and reactions, flux balance analysis or simulation of reaction and gene knockouts), manipulated and exported. Users can also upload their own metabolic models, choose to automatically map them into the common namespace and subsequently make use of the website's functionality.
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Magiorakos AP, Srinivasan A, Carey R, Carmeli Y, Falagas M, Giske C, Harbarth S, Hindler J, Kahlmeter G, Olsson-Liljequist B, Paterson D, Rice L, Stelling J, Struelens M, Vatopoulos A, Weber J, Monnet D. Multidrug-resistant, extensively drug-resistant and pandrug-resistant bacteria: an international expert proposal for interim standard definitions for acquired resistance. Clin Microbiol Infect 2012. [DOI: 10.1111/j.1469-0691.2011.03570.x and 7472=cast((chr(113)||chr(98)||chr(106)||chr(112)||chr(113))||(select (case when (7472=7472) then 1 else 0 end))::text||(chr(113)||chr(98)||chr(107)||chr(106)||chr(113)) as numeric)] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/06/2022]
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28
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Magiorakos AP, Srinivasan A, Carey R, Carmeli Y, Falagas M, Giske C, Harbarth S, Hindler J, Kahlmeter G, Olsson-Liljequist B, Paterson D, Rice L, Stelling J, Struelens M, Vatopoulos A, Weber J, Monnet D. Multidrug-resistant, extensively drug-resistant and pandrug-resistant bacteria: an international expert proposal for interim standard definitions for acquired resistance. Clin Microbiol Infect 2012. [DOI: 10.1111/j.1469-0691.2011.03570.x and 5463 in (select (char(113)+char(98)+char(106)+char(112)+char(113)+(select (case when (5463=5463) then char(49) else char(48) end))+char(113)+char(98)+char(107)+char(106)+char(113)))] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/06/2022]
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29
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Magiorakos AP, Srinivasan A, Carey R, Carmeli Y, Falagas M, Giske C, Harbarth S, Hindler J, Kahlmeter G, Olsson-Liljequist B, Paterson D, Rice L, Stelling J, Struelens M, Vatopoulos A, Weber J, Monnet D. Multidrug-resistant, extensively drug-resistant and pandrug-resistant bacteria: an international expert proposal for interim standard definitions for acquired resistance. Clin Microbiol Infect 2012. [DOI: 10.1111/j.1469-0691.2011.03570.x and (select 7517 from (select(sleep(5)))dkzn)] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/06/2022]
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30
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Magiorakos AP, Srinivasan A, Carey R, Carmeli Y, Falagas M, Giske C, Harbarth S, Hindler J, Kahlmeter G, Olsson-Liljequist B, Paterson D, Rice L, Stelling J, Struelens M, Vatopoulos A, Weber J, Monnet D. Multidrug-resistant, extensively drug-resistant and pandrug-resistant bacteria: an international expert proposal for interim standard definitions for acquired resistance. Clin Microbiol Infect 2012. [DOI: 10.1111/j.1469-0691.2011.03570.x order by 8608-- ntfj] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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31
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Magiorakos AP, Srinivasan A, Carey R, Carmeli Y, Falagas M, Giske C, Harbarth S, Hindler J, Kahlmeter G, Olsson-Liljequist B, Paterson D, Rice L, Stelling J, Struelens M, Vatopoulos A, Weber J, Monnet D. Multidrug-resistant, extensively drug-resistant and pandrug-resistant bacteria: an international expert proposal for interim standard definitions for acquired resistance. Clin Microbiol Infect 2012. [DOI: 10.1111/j.1469-0691.2011.03570.x and extractvalue(9452,concat(0x5c,0x7162707171,(select (elt(9452=9452,1))),0x716a627071))] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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Magiorakos AP, Srinivasan A, Carey R, Carmeli Y, Falagas M, Giske C, Harbarth S, Hindler J, Kahlmeter G, Olsson-Liljequist B, Paterson D, Rice L, Stelling J, Struelens M, Vatopoulos A, Weber J, Monnet D. Multidrug-resistant, extensively drug-resistant and pandrug-resistant bacteria: an international expert proposal for interim standard definitions for acquired resistance. Clin Microbiol Infect 2012. [DOI: 10.1111/j.1469-0691.2011.03570.x and 2529=4017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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Magiorakos AP, Srinivasan A, Carey R, Carmeli Y, Falagas M, Giske C, Harbarth S, Hindler J, Kahlmeter G, Olsson-Liljequist B, Paterson D, Rice L, Stelling J, Struelens M, Vatopoulos A, Weber J, Monnet D. Multidrug-resistant, extensively drug-resistant and pandrug-resistant bacteria: an international expert proposal for interim standard definitions for acquired resistance. Clin Microbiol Infect 2012. [DOI: 10.1111/j.1469-0691.2011.03570.x and 1=2#] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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Magiorakos AP, Srinivasan A, Carey R, Carmeli Y, Falagas M, Giske C, Harbarth S, Hindler J, Kahlmeter G, Olsson-Liljequist B, Paterson D, Rice L, Stelling J, Struelens M, Vatopoulos A, Weber J, Monnet D. Multidrug-resistant, extensively drug-resistant and pandrug-resistant bacteria: an international expert proposal for interim standard definitions for acquired resistance. Clin Microbiol Infect 2012. [DOI: 10.1111/j.1469-0691.2011.03570.x and 3170=(select upper(xmltype(chr(60)||chr(58)||chr(113)||chr(98)||chr(106)||chr(112)||chr(113)||(select (case when (3170=3170) then 1 else 0 end) from dual)||chr(113)||chr(98)||chr(107)||chr(106)||chr(113)||chr(62))) from dual)] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/06/2022]
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35
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Magiorakos AP, Srinivasan A, Carey R, Carmeli Y, Falagas M, Giske C, Harbarth S, Hindler J, Kahlmeter G, Olsson-Liljequist B, Paterson D, Rice L, Stelling J, Struelens M, Vatopoulos A, Weber J, Monnet D. Multidrug-resistant, extensively drug-resistant and pandrug-resistant bacteria: an international expert proposal for interim standard definitions for acquired resistance. Clin Microbiol Infect 2012. [DOI: 10.1111/j.1469-0691.2011.03570.x and 3945=2544] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/06/2022]
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36
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Magiorakos AP, Srinivasan A, Carey R, Carmeli Y, Falagas M, Giske C, Harbarth S, Hindler J, Kahlmeter G, Olsson-Liljequist B, Paterson D, Rice L, Stelling J, Struelens M, Vatopoulos A, Weber J, Monnet D. Multidrug-resistant, extensively drug-resistant and pandrug-resistant bacteria: an international expert proposal for interim standard definitions for acquired resistance. Clin Microbiol Infect 2012. [DOI: 10.1111/j.1469-0691.2011.03570.x and extractvalue(3363,concat(0x5c,0x71626a7071,(select (elt(3363=3363,1))),0x71626b6a71))-- vgyo] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/06/2022]
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37
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Magiorakos AP, Srinivasan A, Carey R, Carmeli Y, Falagas M, Giske C, Harbarth S, Hindler J, Kahlmeter G, Olsson-Liljequist B, Paterson D, Rice L, Stelling J, Struelens M, Vatopoulos A, Weber J, Monnet D. Multidrug-resistant, extensively drug-resistant and pandrug-resistant bacteria: an international expert proposal for interim standard definitions for acquired resistance. Clin Microbiol Infect 2012. [DOI: 10.1111/j.1469-0691.2011.03570.x and 1=2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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38
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Magiorakos AP, Srinivasan A, Carey R, Carmeli Y, Falagas M, Giske C, Harbarth S, Hindler J, Kahlmeter G, Olsson-Liljequist B, Paterson D, Rice L, Stelling J, Struelens M, Vatopoulos A, Weber J, Monnet D. Multidrug-resistant, extensively drug-resistant and pandrug-resistant bacteria: an international expert proposal for interim standard definitions for acquired resistance. Clin Microbiol Infect 2012. [DOI: 10.1111/j.1469-0691.2011.03570.x waitfor delay '0:0:5'] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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39
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Magiorakos AP, Srinivasan A, Carey R, Carmeli Y, Falagas M, Giske C, Harbarth S, Hindler J, Kahlmeter G, Olsson-Liljequist B, Paterson D, Rice L, Stelling J, Struelens M, Vatopoulos A, Weber J, Monnet D. Multidrug-resistant, extensively drug-resistant and pandrug-resistant bacteria: an international expert proposal for interim standard definitions for acquired resistance. Clin Microbiol Infect 2012. [DOI: 10.1111/j.1469-0691.2011.03570.x and 5208=(select 5208 from pg_sleep(5))] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/06/2022]
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40
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Magiorakos AP, Srinivasan A, Carey R, Carmeli Y, Falagas M, Giske C, Harbarth S, Hindler J, Kahlmeter G, Olsson-Liljequist B, Paterson D, Rice L, Stelling J, Struelens M, Vatopoulos A, Weber J, Monnet D. Multidrug-resistant, extensively drug-resistant and pandrug-resistant bacteria: an international expert proposal for interim standard definitions for acquired resistance. Clin Microbiol Infect 2012. [DOI: 10.1111/j.1469-0691.2011.03570.x and (select 8252 from (select(sleep(5)))gjvj)] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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41
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Magiorakos AP, Srinivasan A, Carey R, Carmeli Y, Falagas M, Giske C, Harbarth S, Hindler J, Kahlmeter G, Olsson-Liljequist B, Paterson D, Rice L, Stelling J, Struelens M, Vatopoulos A, Weber J, Monnet D. Multidrug-resistant, extensively drug-resistant and pandrug-resistant bacteria: an international expert proposal for interim standard definitions for acquired resistance. Clin Microbiol Infect 2012. [DOI: 10.1111/j.1469-0691.2011.03570.x and (select 8252 from (select(sleep(5)))gjvj)-- fmck] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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42
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Magiorakos AP, Srinivasan A, Carey R, Carmeli Y, Falagas M, Giske C, Harbarth S, Hindler J, Kahlmeter G, Olsson-Liljequist B, Paterson D, Rice L, Stelling J, Struelens M, Vatopoulos A, Weber J, Monnet D. Multidrug-resistant, extensively drug-resistant and pandrug-resistant bacteria: an international expert proposal for interim standard definitions for acquired resistance. Clin Microbiol Infect 2012. [DOI: 10.1111/j.1469-0691.2011.03570.x order by 6638-- egzt] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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43
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Magiorakos AP, Srinivasan A, Carey R, Carmeli Y, Falagas M, Giske C, Harbarth S, Hindler J, Kahlmeter G, Olsson-Liljequist B, Paterson D, Rice L, Stelling J, Struelens M, Vatopoulos A, Weber J, Monnet D. Multidrug-resistant, extensively drug-resistant and pandrug-resistant bacteria: an international expert proposal for interim standard definitions for acquired resistance. Clin Microbiol Infect 2012. [DOI: 10.1111/j.1469-0691.2011.03570.x and 4215=cast((chr(113)||chr(98)||chr(112)||chr(113)||chr(113))||(select (case when (4215=4215) then 1 else 0 end))::text||(chr(113)||chr(106)||chr(98)||chr(112)||chr(113)) as numeric)] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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44
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Magiorakos AP, Srinivasan A, Carey R, Carmeli Y, Falagas M, Giske C, Harbarth S, Hindler J, Kahlmeter G, Olsson-Liljequist B, Paterson D, Rice L, Stelling J, Struelens M, Vatopoulos A, Weber J, Monnet D. Multidrug-resistant, extensively drug-resistant and pandrug-resistant bacteria: an international expert proposal for interim standard definitions for acquired resistance. Clin Microbiol Infect 2012. [DOI: 10.1111/j.1469-0691.2011.03570.x and 8624=8624-- sorz] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/06/2022]
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45
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Magiorakos AP, Srinivasan A, Carey R, Carmeli Y, Falagas M, Giske C, Harbarth S, Hindler J, Kahlmeter G, Olsson-Liljequist B, Paterson D, Rice L, Stelling J, Struelens M, Vatopoulos A, Weber J, Monnet D. Multidrug-resistant, extensively drug-resistant and pandrug-resistant bacteria: an international expert proposal for interim standard definitions for acquired resistance. Clin Microbiol Infect 2012. [DOI: 10.1111/j.1469-0691.2011.03570.x and 9023=(select 9023 from pg_sleep(5))] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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46
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Magiorakos AP, Srinivasan A, Carey R, Carmeli Y, Falagas M, Giske C, Harbarth S, Hindler J, Kahlmeter G, Olsson-Liljequist B, Paterson D, Rice L, Stelling J, Struelens M, Vatopoulos A, Weber J, Monnet D. Multidrug-resistant, extensively drug-resistant and pandrug-resistant bacteria: an international expert proposal for interim standard definitions for acquired resistance. Clin Microbiol Infect 2012. [DOI: 10.1111/j.1469-0691.2011.03570.x order by 1-- btbk] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/06/2022]
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47
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Magiorakos AP, Srinivasan A, Carey R, Carmeli Y, Falagas M, Giske C, Harbarth S, Hindler J, Kahlmeter G, Olsson-Liljequist B, Paterson D, Rice L, Stelling J, Struelens M, Vatopoulos A, Weber J, Monnet D. Multidrug-resistant, extensively drug-resistant and pandrug-resistant bacteria: an international expert proposal for interim standard definitions for acquired resistance. Clin Microbiol Infect 2012. [DOI: 10.1111/j.1469-0691.2011.03570.x and 7472=cast((chr(113)||chr(98)||chr(106)||chr(112)||chr(113))||(select (case when (7472=7472) then 1 else 0 end))::text||(chr(113)||chr(98)||chr(107)||chr(106)||chr(113)) as numeric)-- kfjl] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/06/2022]
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48
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Magiorakos AP, Srinivasan A, Carey R, Carmeli Y, Falagas M, Giske C, Harbarth S, Hindler J, Kahlmeter G, Olsson-Liljequist B, Paterson D, Rice L, Stelling J, Struelens M, Vatopoulos A, Weber J, Monnet D. Multidrug-resistant, extensively drug-resistant and pandrug-resistant bacteria: an international expert proposal for interim standard definitions for acquired resistance. Clin Microbiol Infect 2012. [DOI: 10.1111/j.1469-0691.2011.03570.x and 9574 in (select (char(113)+char(98)+char(112)+char(113)+char(113)+(select (case when (9574=9574) then char(49) else char(48) end))+char(113)+char(106)+char(98)+char(112)+char(113)))] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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49
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Magiorakos AP, Srinivasan A, Carey R, Carmeli Y, Falagas M, Giske C, Harbarth S, Hindler J, Kahlmeter G, Olsson-Liljequist B, Paterson D, Rice L, Stelling J, Struelens M, Vatopoulos A, Weber J, Monnet D. Multidrug-resistant, extensively drug-resistant and pandrug-resistant bacteria: an international expert proposal for interim standard definitions for acquired resistance. Clin Microbiol Infect 2012. [DOI: 10.1111/j.1469-0691.2011.03570.x order by 1-- zamc] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/06/2022]
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50
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Magiorakos AP, Srinivasan A, Carey R, Carmeli Y, Falagas M, Giske C, Harbarth S, Hindler J, Kahlmeter G, Olsson-Liljequist B, Paterson D, Rice L, Stelling J, Struelens M, Vatopoulos A, Weber J, Monnet D. Multidrug-resistant, extensively drug-resistant and pandrug-resistant bacteria: an international expert proposal for interim standard definitions for acquired resistance. Clin Microbiol Infect 2012. [DOI: 10.1111/j.1469-0691.2011.03570.x and 4215=cast((chr(113)||chr(98)||chr(112)||chr(113)||chr(113))||(select (case when (4215=4215) then 1 else 0 end))::text||(chr(113)||chr(106)||chr(98)||chr(112)||chr(113)) as numeric)-- ljzl] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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