kb_DRAM E. coli annotation
Michael Shaffer
Generated January 5, 2022

kb_DRAM E. coli annotation

Here we are annotating a E. coli K-12 genome using both DRAM and RAST then using those annotations to build models. The genome is from NCBI RefSeq ID NC_000913.

Escherichia_coli_str._K-12_substr._MG1655
v1 - KBaseGenomes.Genome-11.0
The viewer for the data in this Cell is available at the original Narrative here: https://narrative.kbase.us/narrative/103341

Annotate with DRAM

This is a KBase genome object which has already had genes called on it. We will annotate it with DRAM using the "Annotate and Distill Genomes with DRAM" app.

Annotate and Distill Genomes with DRAM
Annotate your genome(s) with DRAM. Annotations will then be distilled to create an interactive functional summary per genome.
This app completed without errors in 42m 37s.
Report
Summary
Here are the results from your DRAM run.
Links
Files
These are only available in the live Narrative: https://narrative.kbase.us/narrative/103341
  • annotations.tsv - DRAM annotations in a tab separate table format
  • genes.faa - Genes as amino acids predicted by DRAM with brief annotations
  • product.tsv - DRAM product in tabular format
  • metabolism_summary.xlsx - DRAM metabolism summary tables
  • genome_stats.tsv - DRAM genome statistics table
Escherichia_coli_str._K-12_substr._MG1655_DRAM
v1 - KBaseGenomes.Genome-11.0
The viewer for the data in this Cell is available at the original Narrative here: https://narrative.kbase.us/narrative/103341

DRAM generates annotations from two separate types: KOs and ECs. The KOs come from annotation with KOfam and the EC's come from KOfam and DBCAN2. To consider all of these annotations at once we must merge them with the "Merge Metaboic Annotations" app.

Merge Metabolic Annotations
Merge multiple metabolic annotations into a single merged annotation based on thresholds
This app completed without errors in 2m 14s.
Objects
Created Object Name Type Description
Escherichia_coli_str._K-12_substr._MG1655_DRAM Genome Genome with merged annotations
Report
Links
Output from Merge Metabolic Annotations
The viewer for the output created by this App is available at the original Narrative here: https://narrative.kbase.us/narrative/103341

Annotate with RAST

Now that we have our genome full annotated with DRAM we can add on the RAST annotations.

Annotate Microbial Genome with RASTtk - v1.073
Annotate or re-annotate bacterial or archaeal genome using RASTtk (Rapid Annotations using Subsystems Technology toolkit).
This app completed without errors in 2m 9s.
Objects
Created Object Name Type Description
Escherichia_coli_str._K-12_substr._MG1655_RAST Genome RAST annotation
Summary 
The RAST algorithm was applied to annotating an existing genome: Escherichia coli str. K-12 substr. MG1655. 
The sequence for this genome is comprised of 1 contigs containing 4641652 nucleotides. 
The input genome has 4355 existing coding features and 1187 existing non-coding features.
Input genome has the following feature types:
	Non-coding gene                  211 
	Non-coding misc_feature           48 
	Non-coding misc_recomb             1 
	Non-coding mobile_element         49 
	Non-coding ncRNA                  72 
	Non-coding rRNA                   22 
	Non-coding rep_origin              1 
	Non-coding repeat_region         697 
	Non-coding tRNA                   86 
	gene                            4355 
The genome features were functionally annotated using the following algorithm(s): Kmers V2; Kmers V1; protein similarity.
In addition to the remaining original 4355 coding features and 1187 non-coding features, 0 new features were called, of which 0 are non-coding.
Output genome has the following feature types:
	Coding gene                     4355 
	Non-coding gene                  211 
	Non-coding misc_feature           48 
	Non-coding misc_recomb             1 
	Non-coding mobile_element         49 
	Non-coding ncRNA                  72 
	Non-coding rRNA                   22 
	Non-coding rep_origin              1 
	Non-coding repeat_region         697 
	Non-coding tRNA                   86 
Overall, the genes have 0 distinct functions. 
The genes include 0 genes with a SEED annotation ontology across 0 distinct SEED functions.
The number of distinct functions can exceed the number of genes because some genes have multiple functions.
Output from Annotate Microbial Genome with RASTtk - v1.073
The viewer for the output created by this App is available at the original Narrative here: https://narrative.kbase.us/narrative/103341

Merge annotations from DRAM and RAST

Then to combine the DRAM annotations with the RAST annotations we can use "Merge Metabolic Annotations" again.

Merge Metabolic Annotations
Merge multiple metabolic annotations into a single merged annotation based on thresholds
This app completed without errors in 2m 15s.
Objects
Created Object Name Type Description
Escherichia_coli_str._K-12_substr._MG1655_RAST_DRAM Genome Genome with merged annotations
Report
Links
Output from Merge Metabolic Annotations
The viewer for the output created by this App is available at the original Narrative here: https://narrative.kbase.us/narrative/103341

Compare annotations

Then we can compare the DRAM, RAST and merged DRAM + RAST annotations.

Compare Metabolic Annotations
Conduct a side-by-side comparison of various metabolic annotations mapped into a genome
This app completed without errors in 1m 18s.
Report
Links

On to modeling!

Now we will build a model for the DRAM annotations, RAST annotations and the merged DRAM + RAST annotations.

Build Metabolic Model
Construct a draft metabolic model based on an annotated genome.
This app completed without errors in 12m 32s.
Objects
Created Object Name Type Description
Escherichia_coli_str._K-12_substr._MG1655_RAST_DRAM_model FBAModel FBAModel-13 Escherichia_coli_str._K-12_substr._MG1655_RAST_DRAM_model
Escherichia_coli_str._K-12_substr._MG1655_RAST_DRAM_model.gf.1 FBA FBA-13 Escherichia_coli_str._K-12_substr._MG1655_RAST_DRAM_model.gf.1
Report
Summary
RefGlucoseMinimal media.
Output from Build Metabolic Model
The viewer for the output created by this App is available at the original Narrative here: https://narrative.kbase.us/narrative/103341
Build Metabolic Model
Construct a draft metabolic model based on an annotated genome.
This app completed without errors in 2m 15s.
Objects
Created Object Name Type Description
Escherichia_coli_str._K-12_substr._MG1655_DRAM_model FBAModel FBAModel-12 Escherichia_coli_str._K-12_substr._MG1655_DRAM_model
Escherichia_coli_str._K-12_substr._MG1655_DRAM_model.gf.1 FBA FBA-13 Escherichia_coli_str._K-12_substr._MG1655_DRAM_model.gf.1
Report
Summary
RefGlucoseMinimal media.
Output from Build Metabolic Model
The viewer for the output created by this App is available at the original Narrative here: https://narrative.kbase.us/narrative/103341
Build Metabolic Model
Construct a draft metabolic model based on an annotated genome.
This app completed without errors in 3m 0s.
Objects
Created Object Name Type Description
Escherichia_coli_str._K-12_substr._MG1655_RAST_model FBAModel FBAModel-13 Escherichia_coli_str._K-12_substr._MG1655_RAST_model
Escherichia_coli_str._K-12_substr._MG1655_RAST_model.gf.1 FBA FBA-13 Escherichia_coli_str._K-12_substr._MG1655_RAST_model.gf.1
Report
Summary
RefGlucoseMinimal media.
Output from Build Metabolic Model
The viewer for the output created by this App is available at the original Narrative here: https://narrative.kbase.us/narrative/103341
Build Metabolic Model
Construct a draft metabolic model based on an annotated genome.
This app completed without errors in 2m 14s.
Objects
Created Object Name Type Description
Escherichia_coli_str._K-12_substr._MG1655_DRAM_KO_model FBAModel FBAModel-12 Escherichia_coli_str._K-12_substr._MG1655_DRAM_KO_model
Escherichia_coli_str._K-12_substr._MG1655_DRAM_KO_model.gf.1 FBA FBA-13 Escherichia_coli_str._K-12_substr._MG1655_DRAM_KO_model.gf.1
Report
Summary
RefGlucoseMinimal media.
Output from Build Metabolic Model
The viewer for the output created by this App is available at the original Narrative here: https://narrative.kbase.us/narrative/103341

Compare models

Now we can compare the models.

Create Model Set Template
Create a template file for Model Comparison app
This app completed without errors in 49s.
Summary
Found 10 objects from 1 narrative
Files
These are only available in the live Narrative: https://narrative.kbase.us/narrative/103341
  • model_comparison_template.xlsx - use this file for Model Comparison app
Import TSV/Excel File as FBAModelSet from Staging Area
Import a TSV or Excel file from your staging area into your Narrative as an Attribute Mapping data object
This app completed without errors in 3m 17s.
Objects
Created Object Name Type Description
model_comparison FBAModelSet Imported FBAModelSet
Summary
Import Finished FBAModelSet Name: model_comparison Imported File: model_comparison_template_e_coli_v5.xlsx
Model Comparison
Retrieve statistical data from models and visualize the comparison via a heatmap
This app is new, and hasn't been started.
No output found.

Characterize models

Characterizing the models will tell us about the metabolic characteristics predicted by each model.

Run Model Characterization
Runs a variety of algorithms on a model to characterize its quality, pathways, and auxotrophy.
This app completed without errors in 5m 47s.
Objects
Created Object Name Type Description
Escherichia_coli_str._K-12_substr._MG1655_RAST_model_characterized.auxo_media Media Media-4 Escherichia_coli_str._K-12_substr._MG1655_RAST_model_characterized.auxo_media
Escherichia_coli_str._K-12_substr._MG1655_RAST_model_characterized FBAModel FBAModel-14 Escherichia_coli_str._K-12_substr._MG1655_RAST_model_characterized
Escherichia_coli_str._K-12_substr._MG1655_RAST_model_characterized.gf.3 FBA FBA-13 Escherichia_coli_str._K-12_substr._MG1655_RAST_model_characterized.gf.3
Escherichia_coli_str._K-12_substr._MG1655_RAST_model_characterized.fba FBA FBA-13 Escherichia_coli_str._K-12_substr._MG1655_RAST_model_characterized.fba
Escherichia_coli_str._K-12_substr._MG1655_RAST_model_characterized.fba FBA FBA-13 Escherichia_coli_str._K-12_substr._MG1655_RAST_model_characterized.fba
Escherichia_coli_str._K-12_substr._MG1655_RAST_model_characterized FBAModel FBAModel-14 Escherichia_coli_str._K-12_substr._MG1655_RAST_model_characterized
Report
Summary
Carbon-D-Glucose media.Carbon-D-Glucose media.Carbon-D-Glucose media.Escherichia_coli_str._K-12_substr._MG1655_RAST_model_characterized.auxo_media media.Complete media.
Output from Run Model Characterization
The viewer for the output created by this App is available at the original Narrative here: https://narrative.kbase.us/narrative/103341
Run Model Characterization
Runs a variety of algorithms on a model to characterize its quality, pathways, and auxotrophy.
This app completed without errors in 4m 46s.
Objects
Created Object Name Type Description
Escherichia_coli_str._K-12_substr._MG1655_DRAM_model_characterized.auxo_media Media Media-4 Escherichia_coli_str._K-12_substr._MG1655_DRAM_model_characterized.auxo_media
Escherichia_coli_str._K-12_substr._MG1655_DRAM_model_characterized FBAModel FBAModel-14 Escherichia_coli_str._K-12_substr._MG1655_DRAM_model_characterized
Escherichia_coli_str._K-12_substr._MG1655_DRAM_model_characterized.gf.3 FBA FBA-13 Escherichia_coli_str._K-12_substr._MG1655_DRAM_model_characterized.gf.3
Escherichia_coli_str._K-12_substr._MG1655_DRAM_model_characterized.fba FBA FBA-13 Escherichia_coli_str._K-12_substr._MG1655_DRAM_model_characterized.fba
Escherichia_coli_str._K-12_substr._MG1655_DRAM_model_characterized.fba FBA FBA-13 Escherichia_coli_str._K-12_substr._MG1655_DRAM_model_characterized.fba
Escherichia_coli_str._K-12_substr._MG1655_DRAM_model_characterized FBAModel FBAModel-14 Escherichia_coli_str._K-12_substr._MG1655_DRAM_model_characterized
Report
Summary
Carbon-D-Glucose media.Carbon-D-Glucose media.Carbon-D-Glucose media.Escherichia_coli_str._K-12_substr._MG1655_DRAM_model_characterized.auxo_media media.Complete media.
Output from Run Model Characterization
The viewer for the output created by this App is available at the original Narrative here: https://narrative.kbase.us/narrative/103341
Run Model Characterization
Runs a variety of algorithms on a model to characterize its quality, pathways, and auxotrophy.
This app completed without errors in 7m 57s.
Objects
Created Object Name Type Description
Escherichia_coli_str._K-12_substr._MG1655_RAST_DRAM_model_characterized.auxo_media Media Media-4 Escherichia_coli_str._K-12_substr._MG1655_RAST_DRAM_model_characterized.auxo_media
Escherichia_coli_str._K-12_substr._MG1655_RAST_DRAM_model_characterized FBAModel FBAModel-14 Escherichia_coli_str._K-12_substr._MG1655_RAST_DRAM_model_characterized
Escherichia_coli_str._K-12_substr._MG1655_RAST_DRAM_model_characterized.gf.3 FBA FBA-13 Escherichia_coli_str._K-12_substr._MG1655_RAST_DRAM_model_characterized.gf.3
Escherichia_coli_str._K-12_substr._MG1655_RAST_DRAM_model_characterized.fba FBA FBA-13 Escherichia_coli_str._K-12_substr._MG1655_RAST_DRAM_model_characterized.fba
Escherichia_coli_str._K-12_substr._MG1655_RAST_DRAM_model_characterized.fba FBA FBA-13 Escherichia_coli_str._K-12_substr._MG1655_RAST_DRAM_model_characterized.fba
Escherichia_coli_str._K-12_substr._MG1655_RAST_DRAM_model_characterized FBAModel FBAModel-14 Escherichia_coli_str._K-12_substr._MG1655_RAST_DRAM_model_characterized
Report
Summary
Carbon-D-Glucose media.Carbon-D-Glucose media.Carbon-D-Glucose media.Escherichia_coli_str._K-12_substr._MG1655_RAST_DRAM_model_characterized.auxo_media media.Complete media.
Output from Run Model Characterization
The viewer for the output created by this App is available at the original Narrative here: https://narrative.kbase.us/narrative/103341
Run Model Characterization
Runs a variety of algorithms on a model to characterize its quality, pathways, and auxotrophy.
This app completed without errors in 5m 23s.
Objects
Created Object Name Type Description
Escherichia_coli_str._K-12_substr._MG1655_DRAM_model_characterized.auxo_media Media Media-4 Escherichia_coli_str._K-12_substr._MG1655_DRAM_model_characterized.auxo_media
Escherichia_coli_str._K-12_substr._MG1655_DRAM_model_characterized FBAModel FBAModel-12 Escherichia_coli_str._K-12_substr._MG1655_DRAM_model_characterized
Escherichia_coli_str._K-12_substr._MG1655_DRAM_model_characterized.gf.3 FBA FBA-13 Escherichia_coli_str._K-12_substr._MG1655_DRAM_model_characterized.gf.3
Escherichia_coli_str._K-12_substr._MG1655_DRAM_model_characterized.fba FBA FBA-13 Escherichia_coli_str._K-12_substr._MG1655_DRAM_model_characterized.fba
Escherichia_coli_str._K-12_substr._MG1655_DRAM_model_characterized.fba FBA FBA-13 Escherichia_coli_str._K-12_substr._MG1655_DRAM_model_characterized.fba
Escherichia_coli_str._K-12_substr._MG1655_DRAM_model_characterized FBAModel FBAModel-12 Escherichia_coli_str._K-12_substr._MG1655_DRAM_model_characterized
Report
Summary
Carbon-D-Glucose media.Carbon-D-Glucose media.Carbon-D-Glucose media.Escherichia_coli_str._K-12_substr._MG1655_DRAM_model_characterized.auxo_media media.Complete media.
Run Model Characterization
Runs a variety of algorithms on a model to characterize its quality, pathways, and auxotrophy.
This app completed without errors in 31m 54s.
Objects
Created Object Name Type Description
Escherichia_coli_str._K-12_substr._MG1655_DRAM_KO_model_characterized.auxo_media Media Media-4 Escherichia_coli_str._K-12_substr._MG1655_DRAM_KO_model_characterized.auxo_media
Escherichia_coli_str._K-12_substr._MG1655_DRAM_KO_model_characterized FBAModel FBAModel-12 Escherichia_coli_str._K-12_substr._MG1655_DRAM_KO_model_characterized
Escherichia_coli_str._K-12_substr._MG1655_DRAM_KO_model_characterized.gf.2 FBA FBA-13 Escherichia_coli_str._K-12_substr._MG1655_DRAM_KO_model_characterized.gf.2
Escherichia_coli_str._K-12_substr._MG1655_DRAM_KO_model_characterized.fba FBA FBA-13 Escherichia_coli_str._K-12_substr._MG1655_DRAM_KO_model_characterized.fba
Escherichia_coli_str._K-12_substr._MG1655_DRAM_KO_model_characterized.fba FBA FBA-13 Escherichia_coli_str._K-12_substr._MG1655_DRAM_KO_model_characterized.fba
Escherichia_coli_str._K-12_substr._MG1655_DRAM_KO_model_characterized FBAModel FBAModel-12 Escherichia_coli_str._K-12_substr._MG1655_DRAM_KO_model_characterized
Report
Summary
Carbon-D-Glucose media.Carbon-D-Glucose media.Carbon-D-Glucose media.Escherichia_coli_str._K-12_substr._MG1655_DRAM_KO_model_characterized.auxo_media media.Complete media.

MEMOTE to evaluate models

Finally we can evaluate all three models with MEMOTE.

Memote - Genome-Scale Model Test Suite
Genome-Scale Model Test Suite
This app completed without errors in 39m 4s.
Report
Links
Files
These are only available in the live Narrative: https://narrative.kbase.us/narrative/103341
  • Escherichia_coli_str._K-12_substr._MG1655_RAST_DRAM_model.xml - desc
Memote - Genome-Scale Model Test Suite
Genome-Scale Model Test Suite
This app completed without errors in 18m 18s.
Report
Links
Files
These are only available in the live Narrative: https://narrative.kbase.us/narrative/103341
  • Escherichia_coli_str._K-12_substr._MG1655_RAST_model.xml - desc
Memote - Genome-Scale Model Test Suite
Genome-Scale Model Test Suite
This app completed without errors in 15m 37s.
Report
Links
Files
These are only available in the live Narrative: https://narrative.kbase.us/narrative/103341
  • Escherichia_coli_str._K-12_substr._MG1655_DRAM_model.xml - desc

Released Apps

  1. Build Metabolic Model
    • [1] Henry CS, DeJongh M, Best AA, Frybarger PM, Linsay B, Stevens RL. High-throughput generation, optimization and analysis of genome-scale metabolic models. Nat Biotechnol. 2010;28: 977 982. doi:10.1038/nbt.1672
    • [2] Overbeek R, Olson R, Pusch GD, Olsen GJ, Davis JJ, Disz T, et al. The SEED and the Rapid Annotation of microbial genomes using Subsystems Technology (RAST). Nucleic Acids Res. 2014;42: D206 D214. doi:10.1093/nar/gkt1226
    • [3] Latendresse M. Efficiently gap-filling reaction networks. BMC Bioinformatics. 2014;15: 225. doi:10.1186/1471-2105-15-225
    • [4] Dreyfuss JM, Zucker JD, Hood HM, Ocasio LR, Sachs MS, Galagan JE. Reconstruction and Validation of a Genome-Scale Metabolic Model for the Filamentous Fungus Neurospora crassa Using FARM. PLOS Computational Biology. 2013;9: e1003126. doi:10.1371/journal.pcbi.1003126
    • [5] Mahadevan R, Schilling CH. The effects of alternate optimal solutions in constraint-based genome-scale metabolic models. Metab Eng. 2003;5: 264 276.
  2. Compare Metabolic Annotations
    no citations
  3. Merge Metabolic Annotations
    • [1] Griesemer M, Kimbrel JA, Zhou CE, Navid A, D'haeseleer P. Combining multiple functional annotation tools increases coverage of metabolic annotation. BMC Genomics. 2018 Dec 19;19(1):948. doi: 10.1186/s12864-018-5221-9.
    • [2] Hanson AD, Pribat A, Waller JC, de Cr cy-Lagard V. Unknown proteins and orphan enzymes: the missing half of the engineering parts list - and how to find it. Biochem J. 2010;425:1 11. doi: 10.1042/BJ20091328.
    • [3] Ijaq J, Chandrasekharan M, Poddar R, Bethi N, Sundararajan VS. Annotation and curation of uncharacterized proteins- challenges. Front Genet. 2015;6:1750. doi: 10.3389/fgene.2015.00119.
    • [4] Land M, Hauser L, Jun S-R, Nookaew I, Leuze MR, Ahn T-H, et al. Insights from 20 years of bacterial genome sequencing. Funct Integr Genomics. 2015;15:141 161. doi: 10.1007/s10142-015-0433-4.
    • [5] Seaver SMD, Liu F, Zhang Q, Jeffryes J, Faria JP, Edirisinghe JN, Mundy M, Chia N, Noor E, Beber ME, Best AA, DeJongh M, Kimbrel JA, D'haeseleer P, McCorkle SR, Bolton JR, Pearson E, Canon S, Wood-Charlson EM, Cottingham RW, Arkin AP, Henry CS. The ModelSEED Biochemistry Database for the integration of metabolic annotations and the reconstruction, comparison and analysis of metabolic models for plants, fungi and microbes. Nucleic Acids Res. 2021 Jan 8;49(D1):D1555. doi: 10.1093/nar/gkaa1143.
  4. Run Model Characterization
    • [1] Henry CS, DeJongh M, Best AA, Frybarger PM, Linsay B, Stevens RL. High-throughput generation, optimization and analysis of genome-scale metabolic models. Nat Biotechnol. 2010;28: 977 982. doi:10.1038/nbt.1672

Apps in Beta

  1. Annotate and Distill Genomes with DRAM
    • DRAM source code
    • DRAM documentation
    • DRAM publication
  2. Annotate Microbial Genome with RASTtk - v1.073
    • [1] Aziz RK, Bartels D, Best AA, DeJongh M, Disz T, Edwards RA, et al. The RAST Server: Rapid Annotations using Subsystems Technology. BMC Genomics. 2008;9: 75. doi:10.1186/1471-2164-9-75
    • [2] Overbeek R, Olson R, Pusch GD, Olsen GJ, Davis JJ, Disz T, et al. The SEED and the Rapid Annotation of microbial genomes using Subsystems Technology (RAST). Nucleic Acids Res. 2014;42: D206 D214. doi:10.1093/nar/gkt1226
    • [3] Brettin T, Davis JJ, Disz T, Edwards RA, Gerdes S, Olsen GJ, et al. RASTtk: A modular and extensible implementation of the RAST algorithm for building custom annotation pipelines and annotating batches of genomes. Sci Rep. 2015;5. doi:10.1038/srep08365
    • [4] Kent WJ. BLAT The BLAST-Like Alignment Tool. Genome Res. 2002;12: 656 664. doi:10.1101/gr.229202
    • [5] Altschul SF, Madden TL, Schaffer AA, Zhang J, Zhang Z, Miller W, Lipman DJ. Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res. 1997;25: 3389-3402. doi:10.1093/nar/25.17.3389
    • [6] Lowe TM, Eddy SR. tRNAscan-SE: a program for improved detection of transfer RNA genes in genomic sequence. Nucleic Acids Res. 1997;25: 955 964.
    • [7] Cobucci-Ponzano B, Rossi M, Moracci M. Translational recoding in archaea. Extremophiles. 2012;16: 793 803. doi:10.1007/s00792-012-0482-8
    • [8] Meyer F, Overbeek R, Rodriguez A. FIGfams: yet another set of protein families. Nucleic Acids Res. 2009;37 6643-54. doi:10.1093/nar/gkp698.
    • [9] van Belkum A, Sluijuter M, de Groot R, Verbrugh H, Hermans PW. Novel BOX repeat PCR assay for high-resolution typing of Streptococcus pneumoniae strains. J Clin Microbiol. 1996;34: 1176 1179.
    • [10] Croucher NJ, Vernikos GS, Parkhill J, Bentley SD. Identification, variation and transcription of pneumococcal repeat sequences. BMC Genomics. 2011;12: 120. doi:10.1186/1471-2164-12-120
    • [11] Hyatt D, Chen G-L, Locascio PF, Land ML, Larimer FW, Hauser LJ. Prodigal: prokaryotic gene recognition and translation initiation site identification. BMC Bioinformatics. 2010;11: 119. doi:10.1186/1471-2105-11-119
    • [12] Delcher AL, Bratke KA, Powers EC, Salzberg SL. Identifying bacterial genes and endosymbiont DNA with Glimmer. Bioinformatics. 2007;23: 673 679. doi:10.1093/bioinformatics/btm009
    • [13] Akhter S, Aziz RK, Edwards RA. PhiSpy: a novel algorithm for finding prophages in bacterial genomes that combines similarity- and composition-based strategies. Nucleic Acids Res. 2012;40: e126. doi:10.1093/nar/gks406
  3. Build Metabolic Model
    • [1] Henry CS, DeJongh M, Best AA, Frybarger PM, Linsay B, Stevens RL. High-throughput generation, optimization and analysis of genome-scale metabolic models. Nat Biotechnol. 2010;28: 977 982. doi:10.1038/nbt.1672
    • [2] Overbeek R, Olson R, Pusch GD, Olsen GJ, Davis JJ, Disz T, et al. The SEED and the Rapid Annotation of microbial genomes using Subsystems Technology (RAST). Nucleic Acids Res. 2014;42: D206 D214. doi:10.1093/nar/gkt1226
    • [3] Latendresse M. Efficiently gap-filling reaction networks. BMC Bioinformatics. 2014;15: 225. doi:10.1186/1471-2105-15-225
    • [4] Dreyfuss JM, Zucker JD, Hood HM, Ocasio LR, Sachs MS, Galagan JE. Reconstruction and Validation of a Genome-Scale Metabolic Model for the Filamentous Fungus Neurospora crassa Using FARM. PLOS Computational Biology. 2013;9: e1003126. doi:10.1371/journal.pcbi.1003126
    • [5] Mahadevan R, Schilling CH. The effects of alternate optimal solutions in constraint-based genome-scale metabolic models. Metab Eng. 2003;5: 264 276.
  4. Create Model Set Template
    no citations
  5. Import TSV/Excel File as FBAModelSet from Staging Area
    no citations
  6. Memote - Genome-Scale Model Test Suite
    no citations
  7. Model Comparison
    no citations
  8. Run Model Characterization
    • [1] Henry CS, DeJongh M, Best AA, Frybarger PM, Linsay B, Stevens RL. High-throughput generation, optimization and analysis of genome-scale metabolic models. Nat Biotechnol. 2010;28: 977 982. doi:10.1038/nbt.1672