Esempio n. 1
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if __name__ == '__main__':

    #- Get all metabolic pathways of all E. coli organisms from KEGG.
    eColiOrganisms = FEV_KEGG.KEGG.Organism.Group(
        searchString='Escherichia coli K-12').organisms

    #- For each organism, combine all pathways to the metabolic network, by UNION operation.
    organismEcGraphs = []
    for organism in eColiOrganisms:
        organismPathways = organism.getMetabolicPathways()
        organismSubstanceReactionGraph = SubstanceReactionGraph.fromPathway(
            organismPathways)

        #- Convert this metabolic network into a substance-ecNumber graph.
        organismSubstanceGeneGraph = SubstanceGeneGraph.fromSubstanceReactionGraph(
            organismSubstanceReactionGraph)
        organismSubstanceEcGraph = SubstanceEcGraph.fromSubstanceGeneGraph(
            organismSubstanceGeneGraph)

        organismEcGraphs.append(organismSubstanceEcGraph)

    firstGraph = organismEcGraphs.pop(0)

    #- Combine all organisms' networks to a consensus network, by INTERSECT operation, leaving only substances and EC numbers that occur in all organisms.
    intersectedEcGraph = firstGraph
    intersectedEcGraph = intersectedEcGraph.intersection(organismEcGraphs)

    #- Print all EC numbers that occur in all organisms.
    output = []
    for ecNumber in intersectedEcGraph.getECs():
        output.append(ecNumber.__str__())
Esempio n. 2
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if __name__ == '__main__':
    
    #- Get all known pathways of eco and sso from KEGG.
    eco = FEV_KEGG.KEGG.Organism.Organism('eco')
    sso = FEV_KEGG.KEGG.Organism.Organism('sso')
    
    ecoPathways = eco.getMetabolicPathways()
    ssoPathways = sso.getMetabolicPathways()
    
    #- Convert each pathway into a substance-ecNumber graph. This is the incomplete metabolic network.
    ecoReactionGraph = SubstanceReactionGraph.fromPathway(ecoPathways)
    ssoReactionGraph = SubstanceReactionGraph.fromPathway(ssoPathways)
    
    ecoGeneGraph = SubstanceGeneGraph.fromSubstanceReactionGraph(ecoReactionGraph)
    ssoGeneGraph = SubstanceGeneGraph.fromSubstanceReactionGraph(ssoReactionGraph)
    
    ecoEnzymeGraph = SubstanceEnzymeGraph.fromSubstanceGeneGraph(ecoGeneGraph)
    ssoEnzymeGraph = SubstanceEnzymeGraph.fromSubstanceGeneGraph(ssoGeneGraph)
    
    #- Remove multifunctional enzymes, meaning enzymes associated with more than one EC number. Helps to reduce false gene duplications.
    ecoEnzymeGraph.removeMultifunctionalEnzymes()
    ssoEnzymeGraph.removeMultifunctionalEnzymes()
    
    ecoEcGraph = SubstanceEcGraph.fromSubstanceEnzymeGraph(ecoEnzymeGraph)
    ssoEcGraph = SubstanceEcGraph.fromSubstanceEnzymeGraph(ssoEnzymeGraph)
    
    #- Combine both species' networks to a consensus network, by INTERSECTION operation.
    intersectionEcGraph = ecoEcGraph.intersection(ssoEcGraph)
    
Esempio n. 3
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from FEV_KEGG.KEGG.Organism import Organism

if __name__ == '__main__':

    #- Download pathway definition as KGML.
    eco = Organism('eco')

    eco00260 = eco.getPathway('00260')
    eco01100 = eco.getPathway('01100')

    #- Convert to substance-reaction graph.
    eco00260_reactionGraph = SubstanceReactionGraph.fromPathway(eco00260)
    eco01100_reactionGraph = SubstanceReactionGraph.fromPathway(eco01100)

    #- Convert to substance-gene graph
    eco00260_geneGraph = SubstanceGeneGraph.fromSubstanceReactionGraph(
        eco00260_reactionGraph)
    eco01100_geneGraph = SubstanceGeneGraph.fromSubstanceReactionGraph(
        eco01100_reactionGraph)

    #- Convert to substance-enzyme graph
    eco00260_enzymeGraph = SubstanceEnzymeGraph.fromSubstanceGeneGraph(
        eco00260_geneGraph)
    eco01100_enzymeGraph = SubstanceEnzymeGraph.fromSubstanceGeneGraph(
        eco01100_geneGraph)

    #- Get set of enzymes for each graph.
    eco00260_enzymes = eco00260_enzymeGraph.getEnzymes()
    eco01100_enzymes = eco01100_enzymeGraph.getEnzymes()

    #- Calculate difference of enzyme sets.
    difference_enzymes = eco00260_enzymes.difference(eco01100_enzymes)
Esempio n. 4
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if __name__ == '__main__':

    #- Download pathway description as KGML.
    eco = Organism('eco')

    eco01100 = eco.getPathway('01100')
    allNonOverviewPathways = eco.getMetabolicPathways(
        includeOverviewMaps=False)

    #- Convert to substance-reaction graph.
    eco01100_reactionGraph = SubstanceReactionGraph.fromPathway(eco01100)
    allNonOverviewPathways_reactionGraph = SubstanceReactionGraph.fromPathway(
        allNonOverviewPathways)

    #- Convert to substance-gene graph.
    eco01100_geneGraph = SubstanceGeneGraph.fromSubstanceReactionGraph(
        eco01100_reactionGraph)
    allNonOverviewPathways_geneGraph = SubstanceGeneGraph.fromSubstanceReactionGraph(
        allNonOverviewPathways_reactionGraph)

    #- Convert to substance-ec graph.
    eco01100_ecGraph = SubstanceEcGraph.fromSubstanceGeneGraph(
        eco01100_geneGraph)
    allNonOverviewPathways_ecGraph = SubstanceEcGraph.fromSubstanceGeneGraph(
        allNonOverviewPathways_geneGraph)

    #- Get set of EC numbers for each graph.
    eco01100_ecNumbers = eco01100_ecGraph.getECs()
    allNonOverviewPathways_ecNumbers = allNonOverviewPathways_ecGraph.getECs()

    #- Calculate difference of EC number sets.
    difference_ecNumbers = eco01100_ecNumbers.difference(