References of "BMC Systems Biology"
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See detailA systems biology investigation of neurodegenerative dementia reveals a pivotal role of autophagy
Caberlotto, Laura; Nguyen, Thanh Phuong UL

in BMC Systems Biology (2014), 8(1), 65

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See detailConsensus and conflict cards for metabolic pathway databases.
Stobbe, Miranda D.; Swertz, Morris A.; Thiele, Ines UL et al

in BMC Systems Biology (2013), 7

BACKGROUND: The metabolic network of H. sapiens and many other organisms is described in multiple pathway databases. The level of agreement between these descriptions, however, has proven to be low. We ... [more ▼]

BACKGROUND: The metabolic network of H. sapiens and many other organisms is described in multiple pathway databases. The level of agreement between these descriptions, however, has proven to be low. We can use these different descriptions to our advantage by identifying conflicting information and combining their knowledge into a single, more accurate, and more complete description. This task is, however, far from trivial. RESULTS: We introduce the concept of Consensus and Conflict Cards (C2Cards) to provide concise overviews of what the databases do or do not agree on. Each card is centered at a single gene, EC number or reaction. These three complementary perspectives make it possible to distinguish disagreements on the underlying biology of a metabolic process from differences that can be explained by different decisions on how and in what detail to represent knowledge. As a proof-of-concept, we implemented C2CardsHuman, as a web application http://www.molgenis.org/c2cards, covering five human pathway databases. CONCLUSIONS: C2Cards can contribute to ongoing reconciliation efforts by simplifying the identification of consensus and conflicts between pathway databases and lowering the threshold for experts to contribute. Several case studies illustrate the potential of the C2Cards in identifying disagreements on the underlying biology of a metabolic process. The overviews may also point out controversial biological knowledge that should be subject of further research. Finally, the examples provided emphasize the importance of manual curation and the need for a broad community involvement. [less ▲]

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See detailGene regulatory network analysis supports inflammation as a key neurodegeneration process in prion disease.
Crespo, Isaac UL; Rump, Kirsten UL; Jurkowski, Wiktor UL et al

in BMC Systems Biology (2012), 6(132),

The activation of immune cells in the brain is believed to be one of the earliest events in prion disease development, where misfolded PrionSc protein deposits are thought to act as irritants leading to a ... [more ▼]

The activation of immune cells in the brain is believed to be one of the earliest events in prion disease development, where misfolded PrionSc protein deposits are thought to act as irritants leading to a series of events that culminate in neuronal cell dysfunction and death. The role of these events in prion disease though is still a matter of debate. To elucidate the mechanisms leading from abnormal protein deposition to neuronal injury, we have performed a detailed network analysis of genes differentially expressed in several mouse prion models [less ▲]

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See detailModel-based clustering reveals vitamin D dependent multi-centrality hubs in a network of vitamin-related proteins
Nguyen, Thanh Phuong UL; Scotti, Marco; Morine, Melissa J. et al

in BMC Systems Biology (2011), 5(1), 195

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See detailThe human metabolic reconstruction Recon 1 directs hypotheses of novel human metabolic functions.
Rolfsson, Ottar; Palsson, Bernhard O.; Thiele, Ines UL

in BMC Systems Biology (2011), 5

BACKGROUND: Metabolic network reconstructions formalize our knowledge of metabolism. Gaps in these networks pinpoint regions of metabolism where biological components and functions are "missing." At the ... [more ▼]

BACKGROUND: Metabolic network reconstructions formalize our knowledge of metabolism. Gaps in these networks pinpoint regions of metabolism where biological components and functions are "missing." At the same time, a major challenge in the post genomic era involves characterisation of missing biological components to complete genome annotation. RESULTS: We used the human metabolic network reconstruction RECON 1 and established constraint-based modelling tools to uncover novel functions associated with human metabolism. Flux variability analysis identified 175 gaps in RECON 1 in the form of blocked reactions. These gaps were unevenly distributed within metabolic pathways but primarily found in the cytosol and often caused by compounds whose metabolic fate, rather than production, is unknown. Using a published algorithm, we computed gap-filling solutions comprised of non-organism specific metabolic reactions capable of bridging the identified gaps. These candidate solutions were found to be dependent upon the reaction environment of the blocked reaction. Importantly, we showed that automatically generated solutions could produce biologically realistic hypotheses of novel human metabolic reactions such as of the fate of iduronic acid following glycan degradation and of N-acetylglutamate in amino acid metabolism. CONCLUSIONS: The results demonstrate how metabolic models can be utilised to direct hypotheses of novel metabolic functions in human metabolism; a process that we find is heavily reliant upon manual curation and biochemical insight. The effectiveness of a systems approach for novel biochemical pathway discovery in mammals is demonstrated and steps required to tailor future gap filling algorithms to mammalian metabolic networks are proposed. [less ▲]

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See detailUnderstanding dynamics using sensitivity analysis: caveat and solution
Perumal, Thanneer Malai UL; Gunawan, Rudiyanto

in BMC Systems Biology (2011), 5

BACKGROUND: Parametric sensitivity analysis (PSA) has become one of the most commonly used tools in computational systems biology, in which the sensitivity coefficients are used to study the parametric ... [more ▼]

BACKGROUND: Parametric sensitivity analysis (PSA) has become one of the most commonly used tools in computational systems biology, in which the sensitivity coefficients are used to study the parametric dependence of biological models. As many of these models describe dynamical behaviour of biological systems, the PSA has subsequently been used to elucidate important cellular processes that regulate this dynamics. However, in this paper, we show that the PSA coefficients are not suitable in inferring the mechanisms by which dynamical behaviour arises and in fact it can even lead to incorrect conclusions. RESULTS: A careful interpretation of parametric perturbations used in the PSA is presented here to explain the issue of using this analysis in inferring dynamics. In short, the PSA coefficients quantify the integrated change in the system behaviour due to persistent parametric perturbations, and thus the dynamical information of when a parameter perturbation matters is lost. To get around this issue, we present a new sensitivity analysis based on impulse perturbations on system parameters, which is named impulse parametric sensitivity analysis (iPSA). The inability of PSA and the efficacy of iPSA in revealing mechanistic information of a dynamical system are illustrated using two examples involving switch activation. CONCLUSIONS: The interpretation of the PSA coefficients of dynamical systems should take into account the persistent nature of parametric perturbations involved in the derivation of this analysis. The application of PSA to identify the controlling mechanism of dynamical behaviour can be misleading. By using impulse perturbations, introduced at different times, the iPSA provides the necessary information to understand how dynamics is achieved, i.e. which parameters are essential and when they become important. [less ▲]

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See detailA community effort towards a knowledge-base and mathematical model of the human pathogen Salmonella Typhimurium LT2.
Thiele, Ines UL; Hyduke, Daniel R.; Steeb, Benjamin et al

in BMC Systems Biology (2011), 5

BACKGROUND: Metabolic reconstructions (MRs) are common denominators in systems biology and represent biochemical, genetic, and genomic (BiGG) knowledge-bases for target organisms by capturing currently ... [more ▼]

BACKGROUND: Metabolic reconstructions (MRs) are common denominators in systems biology and represent biochemical, genetic, and genomic (BiGG) knowledge-bases for target organisms by capturing currently available information in a consistent, structured manner. Salmonella enterica subspecies I serovar Typhimurium is a human pathogen, causes various diseases and its increasing antibiotic resistance poses a public health problem. RESULTS: Here, we describe a community-driven effort, in which more than 20 experts in S. Typhimurium biology and systems biology collaborated to reconcile and expand the S. Typhimurium BiGG knowledge-base. The consensus MR was obtained starting from two independently developed MRs for S. Typhimurium. Key results of this reconstruction jamboree include i) development and implementation of a community-based workflow for MR annotation and reconciliation; ii) incorporation of thermodynamic information; and iii) use of the consensus MR to identify potential multi-target drug therapy approaches. CONCLUSION: Taken together, with the growing number of parallel MRs a structured, community-driven approach will be necessary to maximize quality while increasing adoption of MRs in experimental design and interpretation. [less ▲]

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See detailInferring pleiotropy by network analysis: linked diseases in the human PPI network
Nguyen, Thanh Phuong UL; Liu, Wei-Chung; Jordán, Ferenc

in BMC Systems Biology (2011), 5(1), 179

Background: Earlier, we identified proteins connecting different disease proteins in the human protein-protein interaction network and quantified their mediator role. An analysis of the networks of these ... [more ▼]

Background: Earlier, we identified proteins connecting different disease proteins in the human protein-protein interaction network and quantified their mediator role. An analysis of the networks of these mediators shows that proteins connecting heart disease and diabetes largely overlap with the ones connecting heart disease and obesity. Results: We quantified their overlap, and based on the identified topological patterns, we inferred the structural disease-relatedness of several proteins. Literature data provide a functional look of them, well supporting our findings. For example, the inferred structurally important role of the PDZ domain-containing protein GIPC1 in diabetes is supported despite the lack of this information in the Online Mendelian Inheritance in Man database. Several key mediator proteins identified here clearly has pleiotropic effects, supported by ample evidence for their general but always of only secondary importance. Conclusions: We suggest that studying central nodes in mediator networks may contribute to better understanding and quantifying pleiotropy. Network analysis provides potentially useful tools here, as well as helps in improving databases. [less ▲]

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See detailA detailed genome-wide reconstruction of mouse metabolism based on human Recon 1
Sigurdsson, Martin I.; Jamshidi, Neema; Steingrimsson, Eirikur et al

in BMC Systems Biology (2010), 4

BACKGROUND: Well-curated and validated network reconstructions are extremely valuable tools in systems biology. Detailed metabolic reconstructions of mammals have recently emerged, including human ... [more ▼]

BACKGROUND: Well-curated and validated network reconstructions are extremely valuable tools in systems biology. Detailed metabolic reconstructions of mammals have recently emerged, including human reconstructions. They raise the question if the various successful applications of microbial reconstructions can be replicated in complex organisms. RESULTS: We mapped the published, detailed reconstruction of human metabolism (Recon 1) to other mammals. By searching for genes homologous to Recon 1 genes within mammalian genomes, we were able to create draft metabolic reconstructions of five mammals, including the mouse. Each draft reconstruction was created in compartmentalized and non-compartmentalized version via two different approaches. Using gap-filling algorithms, we were able to produce all cellular components with three out of four versions of the mouse metabolic reconstruction. We finalized a functional model by iterative testing until it passed a predefined set of 260 validation tests. The reconstruction is the largest, most comprehensive mouse reconstruction to-date, accounting for 1,415 genes coding for 2,212 gene-associated reactions and 1,514 non-gene-associated reactions.We tested the mouse model for phenotype prediction capabilities. The majority of predicted essential genes were also essential in vivo. However, our non-tissue specific model was unable to predict gene essentiality for many of the metabolic genes shown to be essential in vivo. Our knockout simulation of the lipoprotein lipase gene correlated well with experimental results, suggesting that softer phenotypes can also be simulated. CONCLUSIONS: We have created a high-quality mouse genome-scale metabolic reconstruction, iMM1415 (Mus Musculus, 1415 genes). We demonstrate that the mouse model can be used to perform phenotype simulations, similar to models of microbe metabolism. Since the mouse is an important experimental organism, this model should become an essential tool for studying metabolic phenotypes in mice, including outcomes from drug screening. [less ▲]

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See detailA quantitative approach to study indirect effects among disease proteins in the human protein interaction network
Nguyen, Thanh Phuong UL; Jordán, Ferenc

in BMC Systems Biology (2010), 4(1), 103

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See detailLocalizing potentially active post-transcriptional regulations in the Ewing's sarcoma gene regulatory network.
Baumuratova, Tatiana UL; Surdez, Didier; Delyon, Bernard et al

in BMC Systems Biology (2010), 4

BACKGROUND: A wide range of techniques is now available for analyzing regulatory networks. Nonetheless, most of these techniques fail to interpret large-scale transcriptional data at the post ... [more ▼]

BACKGROUND: A wide range of techniques is now available for analyzing regulatory networks. Nonetheless, most of these techniques fail to interpret large-scale transcriptional data at the post-translational level. RESULTS: We address the question of using large-scale transcriptomic observation of a system perturbation to analyze a regulatory network which contained several types of interactions - transcriptional and post-translational. Our method consisted of post-processing the outputs of an open-source tool named BioQuali - an automatic constraint-based analysis mimicking biologist's local reasoning on a large scale. The post-processing relied on differences in the behavior of the transcriptional and post-translational levels in the network. As a case study, we analyzed a network representation of the genes and proteins controlled by an oncogene in the context of Ewing's sarcoma. The analysis allowed us to pinpoint active interactions specific to this cancer. We also identified the parts of the network which were incomplete and should be submitted for further investigation. CONCLUSIONS: The proposed approach is effective for the qualitative analysis of cancer networks. It allows the integrative use of experimental data of various types in order to identify the specific information that should be considered a priority in the initial - and possibly very large - experimental dataset. Iteratively, new dataset can be introduced into the analysis to improve the network representation and make it more specific. [less ▲]

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See detailIdentifying potential survival strategies of HIV-1 through virus-host protein interaction networks
Ertaylan, Gökhan UL; van Dijk, D.; Boucher, C. A. et al

in BMC Systems Biology (2010), 15

Background: The National Institute of Allergy and Infectious Diseases has launched the HIV-1 Human Protein Interaction Database in an effort to catalogue all published interactions between HIV-1 and human ... [more ▼]

Background: The National Institute of Allergy and Infectious Diseases has launched the HIV-1 Human Protein Interaction Database in an effort to catalogue all published interactions between HIV-1 and human proteins. In order to systematically investigate these interactions functionally and dynamically, we have constructed an HIV-1 human protein interaction network. This network was analyzed for important proteins and processes that are specific for the HIV life-cycle. In order to expose viral strategies, network motif analysis was carried out showing reoccurring patterns in virus-host dynamics. RESULTS: Our analyses show that human proteins interacting with HIV form a densely connected and central sub-network within the total human protein interaction network. The evaluation of this sub-network for connectivity and centrality resulted in a set of proteins essential for the HIV life-cycle. Remarkably, we were able to associate proteins involved in RNA polymerase II transcription with hubs and proteasome formation with bottlenecks. Inferred network motifs show significant over-representation of positive and negative feedback patterns between virus and host. Strikingly, such patterns have never been reported in combined virus-host systems. CONCLUSIONS: HIV infection results in a reprioritization of cellular processes reflected by an increase in the relative importance of transcriptional machinery and proteasome formation. We conclude that during the evolution of HIV, some patterns of interaction have been selected for resulting in a system where virus proteins preferably interact with central human proteins for direct control and with proteasomal proteins for indirect control over the cellular processes. Finally, the patterns described by network motifs illustrate how virus and host interact with one another. [less ▲]

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See detailMechanism of PP2A-mediated IKK beta dephosphorylation: a systems biological approach.
Witt, Johannes; Barisic, Sandra; Schumann, Eva et al

in BMC Systems Biology (2009), 3

BACKGROUND: Biological effects of nuclear factor-kappaB (NF kappaB) can differ tremendously depending on the cellular context. For example, NF kappaB induced by interleukin-1 (IL-1) is converted from an ... [more ▼]

BACKGROUND: Biological effects of nuclear factor-kappaB (NF kappaB) can differ tremendously depending on the cellular context. For example, NF kappaB induced by interleukin-1 (IL-1) is converted from an inhibitor of death receptor induced apoptosis into a promoter of ultraviolet-B radiation (UVB)-induced apoptosis. This conversion requires prolonged NF kappaB activation and is facilitated by IL-1 + UVB-induced abrogation of the negative feedback loop for NF kappaB, involving a lack of inhibitor of kappaB (I kappaB alpha) protein reappearance. Permanent activation of the upstream kinase IKK beta results from UVB-induced inhibition of the catalytic subunit of Ser-Thr phosphatase PP2A (PP2Ac), leading to immediate phosphorylation and degradation of newly synthesized I kappaB alpha. RESULTS: To investigate the mechanism underlying the general PP2A-mediated tuning of IKK beta phosphorylation upon IL-1 stimulation, we have developed a strictly reduced mathematical model based on ordinary differential equations which includes the essential processes concerning the IL-1 receptor, IKK beta and PP2A. Combining experimental and modelling approaches we demonstrate that constitutively active, but not post-stimulation activated PP2A, tunes out IKK beta phosphorylation thus allowing for I kappaB alpha resynthesis in response to IL-1. Identifiability analysis and determination of confidence intervals reveal that the model allows reliable predictions regarding the dynamics of PP2A deactivation and IKK beta phosphorylation. Additionally, scenario analysis is used to scrutinize several hypotheses regarding the mode of UVB-induced PP2Ac inhibition. The model suggests that down regulation of PP2Ac activity, which results in prevention of I kappaB alpha reappearance, is not a direct UVB action but requires instrumentality. CONCLUSION: The model developed here can be used as a reliable building block of larger NF kappa B models and offers comprehensive simplification potential for future modeling of NF kappa B signaling. It gives more insight into the newly discovered mechanisms for IKK deactivation and allows for substantiated predictions and investigation of different hypotheses. The evidence of constitutive activity of PP2Ac at the IKK complex provides new insights into the feedback regulation of NF kappa B, which is crucial for the development of new anti-cancer strategies. [less ▲]

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See detailA genome-scale metabolic reconstruction of Pseudomonas putida KT2440: iJN746 as a cell factory.
Nogales, Juan; Palsson, Bernhard O.; Thiele, Ines UL

in BMC Systems Biology (2008), 2

BACKGROUND: Pseudomonas putida is the best studied pollutant degradative bacteria and is harnessed by industrial biotechnology to synthesize fine chemicals. Since the publication of P. putida KT2440's ... [more ▼]

BACKGROUND: Pseudomonas putida is the best studied pollutant degradative bacteria and is harnessed by industrial biotechnology to synthesize fine chemicals. Since the publication of P. putida KT2440's genome, some in silico analyses of its metabolic and biotechnology capacities have been published. However, global understanding of the capabilities of P. putida KT2440 requires the construction of a metabolic model that enables the integration of classical experimental data along with genomic and high-throughput data. The constraint-based reconstruction and analysis (COBRA) approach has been successfully used to build and analyze in silico genome-scale metabolic reconstructions. RESULTS: We present a genome-scale reconstruction of P. putida KT2440's metabolism, iJN746, which was constructed based on genomic, biochemical, and physiological information. This manually-curated reconstruction accounts for 746 genes, 950 reactions, and 911 metabolites. iJN746 captures biotechnologically relevant pathways, including polyhydroxyalkanoate synthesis and catabolic pathways of aromatic compounds (e.g., toluene, benzoate, phenylacetate, nicotinate), not described in other metabolic reconstructions or biochemical databases. The predictive potential of iJN746 was validated using experimental data including growth performance and gene deletion studies. Furthermore, in silico growth on toluene was found to be oxygen-limited, suggesting the existence of oxygen-efficient pathways not yet annotated in P. putida's genome. Moreover, we evaluated the production efficiency of polyhydroxyalkanoates from various carbon sources and found fatty acids as the most prominent candidates, as expected. CONCLUSION: Here we presented the first genome-scale reconstruction of P. putida, a biotechnologically interesting all-surrounder. Taken together, this work illustrates the utility of iJN746 as i) a knowledge-base, ii) a discovery tool, and iii) an engineering platform to explore P. putida's potential in bioremediation and bioplastic production. [less ▲]

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See detailArena3D: visualization of biological networks in 3D
Pavlopoulos, Georgios A.; O'Donoghue, Sean I.; Satagopam, Venkata UL et al

in BMC Systems Biology (2008), 2

Background: Complexity is a key problem when visualizing biological networks; as the number of entities increases, most graphical views become incomprehensible. Our goal is to enable many thousands of ... [more ▼]

Background: Complexity is a key problem when visualizing biological networks; as the number of entities increases, most graphical views become incomprehensible. Our goal is to enable many thousands of entities to be visualized meaningfully and with high performance. Results: We present a new visualization tool, Arena3D, which introduces a new concept of staggered layers in 3D space. Related data - such as proteins, chemicals, or pathways - can be grouped onto separate layers and arranged via layout algorithms, such as Fruchterman-Reingold, distance geometry, and a novel hierarchical layout. Data on a layer can be clustered via k-means, affinity propagation, Markov clustering, neighbor joining, tree clustering, or UPGMA ('unweighted pair-group method with arithmetic mean'). A simple input format defines the name and URL for each node, and defines connections or similarity scores between pairs of nodes. The use of Arena3D is illustrated with datasets related to Huntington's disease. Conclusion: Arena3D is a user friendly visualization tool that is able to visualize biological or any other network in 3D space. It is free for academic use and runs on any platform. It can be downloaded or lunched directly from http://arena3d.org. Java3D library and Java 1.5 need to be pre-installed for the software to run. [less ▲]

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