Metabolic modeling has been interwoven with constraing-based methods. The value of randomized sampling in the framework of metabolic modeling has been proved itself over the years (see Schellenberger and Pallson (2009) and Herrmann et al (2019)). Aim of this project is to integrate the produced data and knowledge of these twenty (and more) years and make use of the randomized flux sampling method to evaluate the metabolic interactions retrieved. To this end, thousands of publicly available reference microbial genomes will be selected, and their automatic metabolic network reconstructions will be implemented. Based on these models, cross-feeding interactions algorithms will be performed for groups of species to extract key metabolic processes. New functions, implementing the recently developed Multiphase Monte Carlo Sampling (MMCS) algorithm in the framework of the dingo library, will make use of the randomized flux sampling concept to evaluate the processes retrieved.



Haris Zafeiropoulos


  • Apostolos Chalkis
  • Vissarion Fisikopoulos