@article{GebserSchaubThieleetal.2011,
  author    = {Gebser, Martin and Schaub, Torsten H. and Thiele, Sven and Veber, Philippe},
  title     = {Detecting inconsistencies in large biological networks with answer set programming},
  series = {Theory and practice of logic programming},
  volume    = {11},
  journal   = {Theory and practice of logic programming},
  number    = {5-6},
  publisher = {Cambridge Univ. Press},
  address   = {New York},
  issn      = {1471-0684},
  doi       = {10.1017/S1471068410000554},
  pages     = {323 -- 360},
  year      = {2011},
  abstract  = {We introduce an approach to detecting inconsistencies in large biological networks by using answer set programming. To this end, we build upon a recently proposed notion of consistency between biochemical/genetic reactions and high-throughput profiles of cell activity. We then present an approach based on answer set programming to check the consistency of large-scale data sets. Moreover, we extend this methodology to provide explanations for inconsistencies by determining minimal representations of conflicts. In practice, this can be used to identify unreliable data or to indicate missing reactions.},
  language  = {en}
}
@article{FriouxSchaubSchellhornetal.2019,
  author    = {Frioux, Cl{\´e}mence and Schaub, Torsten H. and Schellhorn, Sebastian and Siegel, Anne and Wanko, Philipp},
  title     = {Hybrid metabolic network completion},
  series = {Theory and practice of logic programming},
  volume    = {19},
  journal   = {Theory and practice of logic programming},
  number    = {1},
  publisher = {Cambridge University Press},
  address   = {New York},
  issn      = {1471-0684},
  doi       = {10.1017/S1471068418000455},
  pages     = {83 -- 108},
  year      = {2019},
  abstract  = {Metabolic networks play a crucial role in biology since they capture all chemical reactions in an organism. While there are networks of high quality for many model organisms, networks for less studied organisms are often of poor quality and suffer from incompleteness. To this end, we introduced in previous work an answer set programming (ASP)-based approach to metabolic network completion. Although this qualitative approach allows for restoring moderately degraded networks, it fails to restore highly degraded ones. This is because it ignores quantitative constraints capturing reaction rates. To address this problem, we propose a hybrid approach to metabolic network completion that integrates our qualitative ASP approach with quantitative means for capturing reaction rates. We begin by formally reconciling existing stoichiometric and topological approaches to network completion in a unified formalism. With it, we develop a hybrid ASP encoding and rely upon the theory reasoning capacities of the ASP system dingo for solving the resulting logic program with linear constraints over reals. We empirically evaluate our approach by means of the metabolic network of Escherichia coli. Our analysis shows that our novel approach yields greatly superior results than obtainable from purely qualitative or quantitative approaches.},
  language  = {en}
}