A. De Martino / Software, tools and additional material
  • A Martirosyan, et al. Translating ceRNA Susceptibilities into Correlation Functions. Biophys J 113:206 (2017) [article]

    • Software and additional material
      Codes implementing the stochastic (Gillespie) simulation: via github;
      Transcriptome analysis: complete results for PTEN ceRNAs available here (see Fig. 10).

  • A Martirosyan, et al. ceRNA crosstalk stabilizes protein expression and affects the correlation pattern of interacting proteins. Sci Rep 7:43673 (2017) [article]

    • Software
      Pipeline implementation for the model shown in Fig. 7 (includes stochastic simulation and computation of the mutual information between input and output nodes): via github

  • J Fernandez de Cossio Diaz, et al. Microenvironmental cooperation promotes early spread and bistability of a Warburg-like phenotype. Sci Rep 7:3103 (2017) [article]

    • Software
      Julia simulation script (complete): via github

  • A Martirosyan, et al. Probing the Limits to MicroRNA-Mediated Control of Gene Expression. PLoS Comp Biol 12:e1004715 (2016) [article]

    • Software and additional material
      Pipeline implementation (includes stochastic simulation and computation of the mutual information between input and output nodes): via github;
      Supporting dataset: here.

  • S Grigolon, et al. Noise Processing by MicroRNA-Mediated Circuits: the Incoherent Feed-Forward Loop, Revisited. Heliyon 2:e00095 (2016) [article]

    • Software
      .zip archive containing C codes for the stochastic (Gillespie) simulations of (a) the standard miRNA-mediated IFLL [fflgillespie.c], (b) the generalized FFL and its limiting circuits upon varying the TF-DNA binding rate [sim_KTF.c], and (c) the generalized FFL and its limiting circuits upon varying transcription rates [simThetaMuThetaMP], together with an auxiliary shell script to run (a) [runffl.sh].

  • F Capuani, et al. Quantitative constraint-based computational model of tumor-to-stroma coupling via lactate shuttle. Sci Rep 5:11880 (2015) [article]

    • Software and stoichiometric matrices
      .tar archive containing a C++ code performing Lovasz-ellypsoid corrected Hit-and-Run Monte Carlo sampling of the feasible space and details of the Human Catabolic Core Networks (both for the cell-autonomous and the two-cell case), including the stoichiometric matrix.

  • A De Martino, et al. Identifying all moiety conservation laws in genome-scale metabolic networks PLoS ONE 9:e100750 (2014) [article]

    • Software and stoichiometric matrices
      C++ code for the computation of moiety conservation laws in genome-scale metabolic networks (general case);
      Test case E. coli iAF1260: stoichiometric matrix and list of metabolites;
      Supporting Text accompanying article: here.

  • FA Massucci, et al. Energy metabolism and glutamate-glutamine cycle in the brain: A stoichiometric modeling perspective. BMC Sys Biol 7:103 (2013) [article]

    • Additional material
      Core metabolic network reconstruction (neuron+glia+intercellular compartment): here

  • D De Martino, et al. Counting and correcting thermodynamically infeasible flux cycles in genome-scale metabolic networks. Metabolites 3:946 (2013) [article]

    • Software and additional material
      C++ code performing cycle identification and removal;
      List of infeasible cycles found in E. coli iAF1260;
      List of infeasible cycles found in 15 Recon-2-derived cell-type specific human metabolic networks.

  • M Figliuzzi, et al. MicroRNAs as a selective channel of communication between competing RNAs: a steady-state theory. Biophys J 104:1203 (2013) [article]

    • Additional material
      Additional results: here

  • A De Martino, et al. Reaction networks as systems for resource allocation: a variational principle for their non-equilibrium steady states. PLoS ONE 7:e39849 (2012) [article]

    • Additional material
      Supporting Tables: here

  • D De Martino, et al. A Scalable Algorithm to Explore the Gibbs energy Landscape of Genome-scale Metabolic Networks. PLOS Comp Biol 8:e1002562 (2012) [article]

    • Software
      C++ code to locate and correct infeasible cycles and compute chemical potentials in genome-scale metabolic networks (implements MinOver)

  • A De Martino, et al. Optimal flux states, reaction replaceability and response to knockouts in the human red blood cell. J Biomed Biotech 2010:415148 (2010) [article]

    • Software and stoichiometric matrices
      stoichiometric matrices (single .tar.gz file incl. input and output matrices);
      optimal flux configurations (a single .tar.gz file with extensive samples for the healthy cell (control) and for various enzyme deficiencies);
      exact enumeration of alternative paths for replaceable metabolic conversions;
      C code to compute optimal fluxes (implements MinOver);
      C code implementing Johnson's circuit-counting algorithm to compute replaceabilities.

  • C Martelli, et al. Identifying essential genes in E. coli from a metabolic optimization principle. PNAS 106:2607 (2009) [article]

    • Additional material
      iJR904-based stoichiometric matrices after leaf removal (1035 reactions x 625 metabolites, single .tar.gz file incl. reversibility and input and output matrices);
      List of metabolites (ordered).