title: YANA - a software tool for analyzing flux modes, gene-expression and enzyme activities.
abstract: BACKGROUND
  A number of algorithms for steady state analysis of metabolic networks have been developed over the years. Of these, Elementary Mode Analysis (EMA) has proven especially useful. Despite its low user-friendliness, METATOOL as a reliable high-performance implementation of the algorithm has been the instrument of choice up to now. As reported here, the analysis of metabolic networks has been improved by an editor and analyzer of metabolic flux modes. Analysis routines for expression levels and the most central, well connected metabolites and their metabolic connections are of particular interest.
  
  
  RESULTS
  YANA features a platform-independent, dedicated toolbox for metabolic networks with a graphical user interface to calculate (integrating METATOOL), edit (including support for the SBML format), visualize, centralize, and compare elementary flux modes. Further, YANA calculates expected flux distributions for a given Elementary Mode (EM) activity pattern and vice versa. Moreover, a dissection algorithm, a centralization algorithm, and an average diameter routine can be used to simplify and analyze complex networks. Proteomics or gene expression data give a rough indication of some individual enzyme activities, whereas the complete flux distribution in the network is often not known. As such data are noisy, YANA features a fast evolutionary algorithm (EA) for the prediction of EM activities with minimum error, including alerts for inconsistent experimental data. We offer the possibility to include further known constraints (e.g. growth constraints) in the EA calculation process. The redox metabolism around glutathione reductase serves as an illustration example. All software and documentation are available for download at http://yana.bioapps.biozentrum.uni-wuerzburg.de.
  
  
  CONCLUSIONS
  A graphical toolbox and an editor for METATOOL as well as a series of additional routines for metabolic network analyses constitute a new user-friendly software for such efforts.
authors.affiliation: Dept of Bioinformatics, Biocenter, University of Würzburg, Germany. roland.schwarz@biozentrum.uni-wuerzburg.de
authors.forename: Roland
authors.initials: R
authors.lastname: Schwarz
authors.forename: Patrick
authors.initials: P
authors.lastname: Musch
authors.forename: Axel
authors.initials: A
authors.lastname: von Kamp
authors.forename: Bernd
authors.initials: B
authors.lastname: Engels
authors.forename: Heiner
authors.initials: H
authors.lastname: Schirmer
authors.forename: Stefan
authors.initials: S
authors.lastname: Schuster
authors.forename: Thomas
authors.initials: T
authors.lastname: Dandekar
mesh_terms: D000465:Algorithms; D000818:Animals; D002468:Cell Physiological Phenomena; D019295:Computational Biology / Q000379:methods*; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D004798:Enzymes / Q000737:chemistry*; D015870:Gene Expression; D020869:Gene Expression Profiling; D005786:Gene Expression Regulation; D023281:Genomics / Q000379:methods; D005980:Glutathione Reductase / Q000378:metabolism; D006801:Humans; D020407:Internet; D008954:Models, Biological; D015233:Models, Statistical; D040901:Proteomics / Q000379:methods; D012984:Software; D012985:Software Design; D018511:Systems Integration; D014158:Transcription, Genetic; D014584:User-Computer Interface
chemical_list: D004798:Enzymes; D005980:Glutathione Reductase