Gapfilling is the process by which the App identifies the minimal set of biochemical reactions to add to a draft metabolic model to enable it to produce biomass in a specified media. This step is optional, but it is recommended and runs by default. A radio box in the advanced options of the Build Metabolic Model App can be unchecked to allow model reconstruction without gapfilling. Gapfilling can be done later if desired. To gapfill the draft metabolic model or to perform additional gapfilling analysis please see the Gapfill Metabolic Model App.
-The quality of a draft metabolic model depends on the completeness of the annotated genome used for the preliminary reconstruction. Due to the fact that most genomes are not completely annotated, draft metabolic models usually contain gaps preventing the production of some biomass components. In this step, an optimization algorithm identifies the minimal set of reactions that must be added to each model to fill these gaps [3, 4]. The gapfilling algorithm is described in detail in the Gapfill Metabolic Model App page. Reactions to be used by gapfilling are selected from the ModelSEED biochemistry database. This curated database contains mass and charge balanced reactions, standardized to aqueous conditions at neutral pH. The ModelSEED reaction database integrates biochemistry contained in KEGG, MetaCyc, EcoCyc, Plant BioCyc, Plant Metabolic Networks, and Gramene. This step is conducted to ensure that every model is capable of simulating cell growth.
+The quality of a draft metabolic model depends on the completeness of the annotated genome used for the preliminary reconstruction. Due to the fact that most genomes are not completely annotated, draft metabolic models usually contain gaps preventing the production of some biomass components. In this step, an optimization algorithm identifies the minimal set of reactions that must be added to each model to fill these gaps [3, 4]. The gapfilling algorithm is described in detail in the Gapfill Metabolic Model App page. Reactions to be used by gapfilling are selected from the ModelSEED biochemistry database. This curated database contains mass and charge balanced reactions, standardized to aqueous conditions at neutral pH. The ModelSEED reaction database integrates biochemistry contained in KEGG, MetaCyc, EcoCyc, Plant Metabolic Networks, and Gramene. This step is conducted to ensure that every model is capable of simulating cell growth.
Once model reconstruction is complete, Flux Balance Analysis (FBA) can be applied to assess the capacity of reactions to carry flux and reaction essentiality.
diff --git a/ui/narrative/methods/build_metabolic_model/spec.json b/ui/narrative/methods/build_metabolic_model/spec.json index f4b3187..47f37ba 100644 --- a/ui/narrative/methods/build_metabolic_model/spec.json +++ b/ui/narrative/methods/build_metabolic_model/spec.json @@ -85,12 +85,6 @@ "ui_name" : "Gram positive", "display" : "Gram positive" }, - { - "display" : "Plant", - "ui_name" : "Plant", - "value" : "plant", - "id" : "plant" - }, { "display" : "Core metabolism", "ui_name" : "Core metabolism", diff --git a/ui/narrative/methods/build_multiple_metabolic_models/display.yaml b/ui/narrative/methods/build_multiple_metabolic_models/display.yaml index ae6fa66..4473184 100644 --- a/ui/narrative/methods/build_multiple_metabolic_models/display.yaml +++ b/ui/narrative/methods/build_multiple_metabolic_models/display.yaml @@ -72,7 +72,7 @@ parameters : ui-name : | Template for reconstruction short-hint : | - Models are generated based on a default template model in KBase. Template models capture the necessary biochemical information based on user-defined scope. KBase primarily uses four template models: (i) Gram positive microbe, (ii) Gram negative microbe, (iii) Core pathways microbe, and (iv) Plant. These template models differ from each other by biomass composition and biochemical reaction functional associations. + Models are generated based on a default template model in KBase. Template models capture the necessary biochemical information based on user-defined scope. KBase primarily uses four template models: (i) Gram positive microbe, (ii) Gram negative microbe, and (iii) Core pathways microbe. These template models differ from each other by biomass composition and biochemical reaction functional associations. media_supplement_list : ui-name : | @@ -102,7 +102,7 @@ description : |
Gapfilling is the process by which the App identifies the minimal set of biochemical reactions to add to a draft metabolic model to enable it to produce biomass in a specified media.This step is optional, but it is recommended and runs by default. A radio box in the advanced options of the Build Multiple Metabolic Models App can be unchecked to allow model reconstruction without gapfilling. Gapfilling can be done later if desired. To gapfill the draft metabolic model or to perform additional gapfilling analysis please see the Gapfill Metabolic Model App.
-The quality of each draft metabolic model depends on the completeness of the annotated genomes used for the preliminary reconstruction. Due to the fact that most genomes are not completely annotated, draft metabolic models usually contain gaps preventing the production of some biomass components. In this step, an optimization algorithm identifies the minimal set of reactions that must be added to each model to fill these gaps [3, 4]. The gapfilling algorithm is described in detail in the Gapfill Metabolic Model App page. Reactions to be used by gapfilling are selected from the ModelSEED biochemistry database. This curated database contains mass and charge balanced reactions, standardized to aqueous conditions at neutral pH. The ModelSEED reaction database integrates biochemistry contained KEGG, MetaCyc, EcoCyc, Plant BioCyc, Plant Metabolic Networks, and Gramene. This step is conducted to ensure that every model is capable of simulating cell growth.
+The quality of each draft metabolic model depends on the completeness of the annotated genomes used for the preliminary reconstruction. Due to the fact that most genomes are not completely annotated, draft metabolic models usually contain gaps preventing the production of some biomass components. In this step, an optimization algorithm identifies the minimal set of reactions that must be added to each model to fill these gaps [3, 4]. The gapfilling algorithm is described in detail in the Gapfill Metabolic Model App page. Reactions to be used by gapfilling are selected from the ModelSEED biochemistry database. This curated database contains mass and charge balanced reactions, standardized to aqueous conditions at neutral pH. The ModelSEED reaction database integrates biochemistry contained KEGG, MetaCyc, EcoCyc, Plant Metabolic Networks, and Gramene. This step is conducted to ensure that every model is capable of simulating cell growth.
Once model reconstruction is complete, the Flux Balance Analysis (FBA) can be applied to assess the capacity of reactions to carry flux and reaction essentiality.
diff --git a/ui/narrative/methods/build_multiple_metabolic_models/spec.json b/ui/narrative/methods/build_multiple_metabolic_models/spec.json index 9c2f9b6..74b4f8a 100644 --- a/ui/narrative/methods/build_multiple_metabolic_models/spec.json +++ b/ui/narrative/methods/build_multiple_metabolic_models/spec.json @@ -79,12 +79,6 @@ "ui_name" : "Gram positive", "display" : "Gram positive" }, - { - "display" : "Plant", - "ui_name" : "Plant", - "value" : "plant", - "id" : "plant" - }, { "display" : "Core metabolism", "ui_name" : "Core metabolism",