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view tools/networkAnalysis/ChokePoint/ChokePoint.xml @ 8:1274e2a62479 draft default tip
planemo upload for repository https://forgemia.inra.fr/metexplore/met4j-galaxy commit e34acf0f51cafcf6ae7c97b4feb3188a39f17c32
author | metexplore |
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date | Wed, 26 Jul 2023 15:33:45 +0000 |
parents | 1436e9cde9c9 |
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<?xml version="1.0" encoding="UTF-8"?> <tool id="met4j_ChokePoint" name="ChokePoint" version="MET4J_VERSION_TEST"> <description>Compute the Choke points of a metabolic network.</description> <xrefs> <xref type="bio.tools">met4j</xref> </xrefs> <requirements> <container type="singularity">oras://registry.forgemia.inra.fr/metexplore/met4j/met4j-singularity:MET4J_VERSION_TEST</container> </requirements> <command detect_errors="exit_code"><![CDATA[sh /usr/bin/met4j.sh networkAnalysis.ChokePoint -i "$inputPath" -o "$outputPath" ]]></command> <inputs> <param argument="-i" format="sbml" label="input SBML file" name="inputPath" optional="false" type="data" value=""/> </inputs> <outputs> <data format="tsv" name="outputPath"/> </outputs> <tests> <test> <param name="inputPath" value="XF_network.sbml"/> <output ftype="tsv" name="outputPath"> <assert_contents> <has_n_lines n="695"/> <has_n_columns n="3"/> <has_line_matching expression="R_ADEtex.*adenine_transport_via_diffusion__extracellular_to_periplasm_.*M_ade_e <==> M_ade_p" n="1"/> <has_line_matching expression="R_AGDC_r.*R_AGDC_r.*M_acgam6p_c \+ M_h2o_c --> M_ac_c \+ M_gam6p_c" n="1"/> </assert_contents> </output> </test> </tests> <help><![CDATA[Compute the Choke points of a metabolic network. Choke points constitute an indicator of lethality and can help identifying drug target Choke points are reactions that are required to consume or produce one compound. Targeting of choke point can lead to the accumulation or the loss of some metabolites, thus choke points constitute an indicator of lethality and can help identifying drug target See : Syed Asad Rahman, Dietmar Schomburg; Observing local and global properties of metabolic pathways: ‘load points’ and ‘choke points’ in the metabolic networks. Bioinformatics 2006; 22 (14): 1767-1774. doi: 10.1093/bioinformatics/btl181]]></help> <citations/> </tool>