Informed curation and gapfilling of metabolic networks

1. Needed input files

• Genome (fna)
• Draft model (xml)

2. Seed database corrections

• python3 src/seedcorrect.py dat/myb71.xml

3. Obtaining candidate reactions

• ./gapseq.sh -p core dat/myb71.fna
• ./gapseq.sh -p degradation dat/myb71.fna
• ./transporter.sh dat/myb71.fna

4. Gapfilling

• Rscript gf.suite.R -m ./dat/myb71_corrected.xml -c ./dat/myb71-core-Reactions.lst,dat/myb71-degradation-Reactions.lst,dat/myb71-Transporter.lst -n dat/media/TSBmed.csv