title: DISTING: A web application for fast algorithmic computation of alternative indistinguishable linear compartmental models.
abstract: OBJECTIVE
  We describe and illustrate use of DISTING, a novel web application for computing alternative structurally identifiable linear compartmental models that are input-output indistinguishable from a postulated linear compartmental model. Several computer packages are available for analysing the structural identifiability of such models, but DISTING is the first to be made available for assessing indistinguishability.
  
  
  METHODS
  The computational algorithms embedded in DISTING are based on advanced versions of established geometric and algebraic properties of linear compartmental models, embedded in a user-friendly graphic model user interface. Novel computational tools greatly speed up the overall procedure. These include algorithms for Jacobian matrix reduction, submatrix rank reduction, and parallelization of candidate rank computations in symbolic matrix analysis.
  
  
  RESULTS
  The application of DISTING to three postulated models with respectively two, three and four compartments is given. The 2-compartment example is used to illustrate the indistinguishability problem; the original (unidentifiable) model is found to have two structurally identifiable models that are indistinguishable from it. The 3-compartment example has three structurally identifiable indistinguishable models. It is found from DISTING that the four-compartment example has five structurally identifiable models indistinguishable from the original postulated model. This example shows that care is needed when dealing with models that have two or more compartments which are neither perturbed nor observed, because the numbering of these compartments may be arbitrary.
  
  
  CONCLUSIONS
  DISTING is universally and freely available via the Internet. It is easy to use and circumvents tedious and complicated algebraic analysis previously done by hand.
authors.affiliation: Biocybernetics Laboratory, Computer Science Department, University of California Los Angeles, CA 90095, U.S.A.
authors.forename: Natalie R
authors.initials: NR
authors.lastname: Davidson
authors.affiliation: School of Engineering, University of Warwick, Coventry, CV4 7AL, U.K.. Electronic address: k.godfrey@warwick.ac.uk.
authors.forename: Keith R
authors.initials: KR
authors.lastname: Godfrey
authors.affiliation: Biocybernetics Laboratory, Computer Science Department, University of California Los Angeles, CA 90095, U.S.A.
authors.forename: Faisal
authors.initials: F
authors.lastname: Alquaddoomi
authors.affiliation: Biocybernetics Laboratory, Computer Science Department, University of California Los Angeles, CA 90095, U.S.A.
authors.forename: David
authors.initials: D
authors.lastname: Nola
authors.affiliation: Biocybernetics Laboratory, Computer Science Department, University of California Los Angeles, CA 90095, U.S.A.
authors.forename: Joseph J
authors.initials: JJ
authors.lastname: DiStefano
mesh_terms: D000465:Algorithms; D003196:Computer Graphics; D003198:Computer Simulation; D006801:Humans; D020407:Internet; D016014:Linear Models; D008099:Liver / Q000187:drug effects; D004364:Pharmaceutical Preparations; D012984:Software; D013448:Sulfobromophthalein / Q000737:chemistry; D049490:Systems Biology
chemical_list: D004364:Pharmaceutical Preparations; D013448:Sulfobromophthalein
keywords: Compartmental modeling; Model selection; Parallel computing; Structural identifiability; Symbolic algebra