23 research outputs found

    The rules for adding GPRs.

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    <p>Reaction1 is catalyzed by a modifier which is a multiprotein complex of gene1 and gene2. The combination of both the genes are required for the reaction to take place. Reaction2 is inhibited in presence of inhibitor which is an isoform of gene3 and gene4. Presence of either gene3 or gene4 will inhibit Reaction2. A ‘NOT’ operator is assigned to the GPR of Reaction2 to indicate inhibition. A GPR is not assigned to Reaction 3 in this example.</p

    The pipeline used to determine the effects of active AKT signaling on the EMT metabolic network.

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    <p>The metabolic genes predicted to be altered in D492 and D492M dependent on the AKT signaling network, were used to constrain the EMT metabolic network generated from Recon2, in order to identify downstream metabolic pathways that are affected by AKT activation.</p

    Sub-network of EGFR_SN network.

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    <p>A part of the EGFR signaling network representing AKT signaling. Nodes indicate the reacting component and edges denote the reactions. Red nodes indicate inhibitors which were manually added to the model in the form of GPRs (information obtained from the Reactome database), white nodes indicate signaling components present in the original SBML file downloaded from the Reactome database and green nodes indicate exchange reactions which were added to the model to remove dead ends. Node ‘B’ and ‘P’ indicates binding, and phosphorylation, respectively. Edges: → transition, ⟞ inhibition, ⫯ catalysis.</p

    Flux differences between epithelial network (EGFR_E) and mesenchymal network (EGFR_M).

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    <p>A) Probability density estimates for the flux values in selected reactions as obtained by random sampling. The blue curve represents the flux distribution of EGFR_E and the red curve that of EGFR_M. Vertical axis denote probability and flux values are represented on the horizontal axis. AU: arbitrary units B) Relative mean flux for each reaction in EGFR_E and EGFR_M through the AKT, RAS and DAG/IP3 and CaM pathways. Higher flux within reactions in AKT and RAS/MAPK pathways are observed in the EGFR_E network compared to EGFR_M while CaM and DAG/IP3 have higher flux in EGFR_M. Negative values denote higher flux in EGFR_E and positive values denotes higher flux in EGFR_M. Numerical values of these fluxes are given in supplementary file (<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1004924#pcbi.1004924.s002" target="_blank">S1 File</a>).</p

    Proliferation rate and glycolytic activity are higher in D492 than in D492M cells.

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    <p>A) Cell proliferation assay demonstrated a higher growth rate of D492 cells compared to D492M cells. B) Spent medium analysis of glucose (dashed lines) and lactate (solid lines) shows higher glucose uptake and lactate secretion in D492 cells (blue) than in D492M cells (red). C) Calculated glucose uptake and lactate secretion rates indicate higher glycolytic flux rates per cell per hour in D492 cells than D492M cells. Data represents results from 3 independent experiments. Error bars represent standard deviation in a single experiment done in triplicate. mM: milli molar, fmol: femto molar.</p

    Unusual comQXPA-like loci.

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    <p>(A) Non-canonical unusual <i>com</i> system is present in <i>B. cereus</i> VD102, <i>B. cereus</i> BAG4X12 1, <i>B. cereus</i> MSX A1 and <i>L. fusiformis</i> ZC1. Note that <i>Lysinibacillus</i> is the only genus whose two species have two <i>com</i> loci each: <i>L. sphaericus</i> C3 41 has two canonical loci while in <i>L. fusiformis</i> ZC1 one locus is canonical and the other one is non-canonical, shown here. (B) Canonical unusual <i>com</i> system present in <i>Paenibacillus curdlanolyticus</i> YK9 and <i>B. coagulans</i> 36D1.</p
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