MetNetComp Database [1] / Minimal gene deletions

Minimal gene deletions for simulation-based growth-coupled production. You can also see maximal gene deletions.

Model : iMM904 [2].
Target metabolite : cdpea_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (66 of 69: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 31
  Gene deletion: YDL168W YMR303C YBR068C YDR046C YBR069C YPL061W YGR087C YLR044C YLR134W YDR380W YDL080C YKL192C YNL141W YNR033W YOL052C YNL111C YHR002W YCL025C YKR039W YOL020W YOR120W YOL059W YGR191W YJR078W YJL121C YLR348C YPL092W YML120C YBR180W YLR328W YOR155C   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.107325 (mmol/gDw/h)
  Minimum Production Rate : 0.001180 (mmol/gDw/h)

 Substrate: (mmol/gDw/h)
  EX_glc__D_e : 10.000000
  EX_o2_e : 2.000000
  EX_nh4_e : 1.365645
  EX_pi_e : 0.035878
  EX_so4_e : 0.008296

Product: (mmol/gDw/h)
  EX_h_e : 23.089204
  EX_h2o_e : 13.283167
  EX_succ_e : 7.261185
  EX_3c3hmp_e : 3.632470
  EX_gly_e : 0.322898
  EX_etoh_e : 0.220682
  EX_xan_e : 0.101659
  EX_pap_e : 0.006150
  Auxiliary production reaction : 0.001180
  EX_for_e : 0.000555

Visualization
  1. Download JSON file.
  2. Go to Escher site [3].
  3. Select "Data > Load reaction data" and apply the downloaded file.

References
[1] Tamura, T. MetNetComp: Database for minimal and maximal gene deletion strategies for growth-coupled production of genome-scale metabolic networks, IEEE/ACM Transactions on Computational Biology and Bioinformatics, in press.
[2] Norsigian, C. J., Pusarla, N., McConn, J. L., Yurkovich, J. T., Dräger, A., Palsson, B. O., & King, Z. (2020). BiGG Models 2020: multi-strain genome-scale models and expansion across the phylogenetic tree. Nucleic acids research, 48(D1), D402-D406.
[3] King, Z. A., Dräger, A., Ebrahim, A., Sonnenschein, N., Lewis, N. E., & Palsson, B. O. (2015). Escher: a web application for building, sharing, and embedding data-rich visualizations of biological pathways. PLoS computational biology, 11(8), e1004321.

Last updated: 27-Sep-2023
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