MOTIVATION: Elementary modes (EMs) and minimal cut sets (MCSs) provide important techniques for metabolic network modeling. Whereas EMs describe minimal subnetworks that can function in steady state, MCSs are sets of reactions whose removal will disable certain network functions. Effective algorithms were developed for EM computation while calculation of MCSs is typically addressed by indirect methods requiring the computation of EMs as initial step. RESULTS: In this contribution, we provide a method that determines MCSs directly without calculating the EMs. We introduce a duality framework for metabolic networks where the enumeration of MCSs in the original network is reduced to identifying the EMs in a dual network. As a further extension, we propose a generalization of MCSs in metabolic networks by allowing the combination of inhomogeneous constraints on reaction rates. This framework provides a promising tool to open the concept of EMs and MCSs to a wider class of applications. CONTACT: utz-uwe.haus@math.ethz.ch; klamt@mpi-magdeburg.mpg.de SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
MOTIVATION: Elementary modes (EMs) and minimal cut sets (MCSs) provide important techniques for metabolic network modeling. Whereas EMs describe minimal subnetworks that can function in steady state, MCSs are sets of reactions whose removal will disable certain network functions. Effective algorithms were developed for EM computation while calculation of MCSs is typically addressed by indirect methods requiring the computation of EMs as initial step. RESULTS: In this contribution, we provide a method that determines MCSs directly without calculating the EMs. We introduce a duality framework for metabolic networks where the enumeration of MCSs in the original network is reduced to identifying the EMs in a dual network. As a further extension, we propose a generalization of MCSs in metabolic networks by allowing the combination of inhomogeneous constraints on reaction rates. This framework provides a promising tool to open the concept of EMs and MCSs to a wider class of applications. CONTACT: utz-uwe.haus@math.ethz.ch; klamt@mpi-magdeburg.mpg.de SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Authors: Laurent Heirendt; Sylvain Arreckx; Thomas Pfau; Sebastián N Mendoza; Anne Richelle; Almut Heinken; Hulda S Haraldsdóttir; Jacek Wachowiak; Sarah M Keating; Vanja Vlasov; Stefania Magnusdóttir; Chiam Yu Ng; German Preciat; Alise Žagare; Siu H J Chan; Maike K Aurich; Catherine M Clancy; Jennifer Modamio; John T Sauls; Alberto Noronha; Aarash Bordbar; Benjamin Cousins; Diana C El Assal; Luis V Valcarcel; Iñigo Apaolaza; Susan Ghaderi; Masoud Ahookhosh; Marouen Ben Guebila; Andrejs Kostromins; Nicolas Sompairac; Hoai M Le; Ding Ma; Yuekai Sun; Lin Wang; James T Yurkovich; Miguel A P Oliveira; Phan T Vuong; Lemmer P El Assal; Inna Kuperstein; Andrei Zinovyev; H Scott Hinton; William A Bryant; Francisco J Aragón Artacho; Francisco J Planes; Egils Stalidzans; Alejandro Maass; Santosh Vempala; Michael Hucka; Michael A Saunders; Costas D Maranas; Nathan E Lewis; Thomas Sauter; Bernhard Ø Palsson; Ines Thiele; Ronan M T Fleming Journal: Nat Protoc Date: 2019-03 Impact factor: 13.491