Resource page for chimera's quantitative
biology research activity


(Last updated : June 2015)
                   


                   



          
Supporting materials
        
        
  • F Capuani, D De Martino, E Marinari and A De Martino. Quantitative constraint-based computational model of tumor-to-stroma coupling via lactate shuttle. Sci Rep (to appear, 2015)
    • Supporting material
      .tar archive containing a C++ code performing Lovasz H&R Monte Carlo and details of the HCCN networks (cell-autonomous and two cells)

  • A De Martino, D De Martino, R Mulet and A Pagnani, Identifying all moiety conservation laws in genome-scale metabolic networks PLOS ONE 9:e100750 (2014) [journal, arXiv]
    • Supporting material
      C++ code for the computation of moiety conservation laws in genome-scale metabolic networks
      Test case: E. coli iAF1260 stoichiometric matrix and metabolites' list
      Supporting Text accompanying article, see here

  • FA Massucci, M Di Nuzzo, F Giove, B Maraviglia, I Perez Castillo, E Marinari and A De Martino, Energy metabolism and glutamate-glutamine cycle in the brain: A stoichiometric modeling perspective. BMC Sys Biol 7:103 (2013) [journal, arXiv]
    • Supporting material
      Supporting Text accompanying article, see here or here

  • D De Martino, F Capuani, M Mori, A De Martino and E Marinari, Counting and correcting thermodynamically infeasible flux cycles in genome-scale metabolic networks. Metabolites 3:946 (2013) [journal, arXiv]
    • Supporting material
      List of cycles found in E.coli iAF1260
      List of cycles found in the Recon-2 derived cell-type specific networks
      C++ code performing cycle identification and removal

  • M Figliuzzi, E Marinari and A De Martino, MicroRNAs as a selective channel of communication between competing RNAs: a steady-state theory. Biophys J 104:1203 (2013) [journal, arXiv]
    • Supporting material
      Supporting Text accompanying article, see here or here

  • A De Martino, D De Martino, R Mulet and G Uguzzoni, Reaction networks as systems for resource allocation: a variational principle for their non-equilibrium steady states. PLOS ONE 7:e39849 (2012) [journal, arXiv]
  • D De Martino, M Figliuzzi, A De Martino, and E Marinari, A Scalable Algorithm to Explore the Gibbs energy Landscape of Genome-scale Metabolic Networks. PLOS Comp Biol 8:e1002562 (2012) [journal, arXiv]
    • Supporting material
      A C++ code to locate and correct infeasible cycles and compute chemical potentials in metabolic networks (via MinOver)

  • A De Martino, D Granata, E Marinari, C Martelli, and V Van Kerrebroeck, Optimal flux states, reaction replaceability and response to knockouts in the human red blood cell. J Biomed Biotech 2010:415148 (2010) [journal, arXiv]
    • Supporting material
      stoichiometric matrices (single .tar.gz file incl. input and output matrices)
      optimal flux configurations (a single .tar.gz file with large samples for the healthy cell and for various enzyme deficiencies)
      enumeration of alternative paths for replaceable metabolic conversions
      a C code to compute optimal fluxes (via MinOver)
      a C code implementing Johnson's circuit-counting algorithm to compute replaceabilities

  • C Martelli, A De Martino, E Marinari, M Marsili, and I Perez Castillo, Identifying essential genes in E. coli from a metabolic optimization principle. PNAS 106:2607 (2009) [journal, arXiv]
    • Supporting material
      stoichiometric matrices after leaf removal, reversibility included (1035 reactions x 625 metabolites, single .tar.gz file incl. input and output matrices)
      list of the 625 chemical species, ordered as in the stoichiometric matrices