3 Biochemical NetworksSimple Network:Data:ABC + DEB + 2 FG +H
4 Modeling Paradigm Top Down Bottom Up Phenomenological modeling approach describing experimental data.Bottom UpSmall well understood models, e.g. enzymatic reactions are used to comprise larger models.
5 What we need? Easy to use analysis tools Interaction between tools Simulation with trusted resultsParameter estimation capabilitiesModel comparison.
6 COPASI Features Time Course Steady State Structural Analysis Metabolic Control AnalysisLyapunov Exponent CalculationParameter ScanOptimizationParameter Fitting
7 ODE Based Time Course Simulation -1 0 01 0 -10 -1 00 1 00 0 -20 0 1A BCDEFGH.=v 1 (A, B, H)v 2 (B, C, D, E)v 3 (B, E, F, G, H)x = N v with:.v =v 1 v 2v mx =x 1 x 2x nIn general:
8 Stochastic Time Course Simulation Initialize systemCalculate: Reaction probabilitiesGenerate random numbers to determine:time of next reactionwhich reaction happensUpdate the system the systemExample
9 OptimizationOptimization attempts to maximize or minimize an objective function.Note, that the maximum of a function f is equivalent to the minimum –fGiven a real-valued scalar function f(x,k) of n parameters k=(k1, ..., kn) find a minimum of f(x,k) such that:gi(x) ≥ 0 with i=1,..., m (inequality constraints)hj(x) = 0 with j=1,..., m’ (equality constraints)
14 Command Line Interface Suitable for long computational task like Optimization or Parameter EstimationBackground progress for Web-applications or Web-servicesBasic usage:Create a model with the COPASI GUISpecify computational task in the GUISave File “model.cps”CopasiSE “model.cps”
15 Available Platforms Linux All WIN32 OS starting Windows 98 (Intel) Mac OS X (PowerPC and Intel)SunOS starting with Solaris 8 (sparc)Achieved throughQT (Toolkit and libraries for GUI development)LAPACK / BLAS (matrix and vector routines)ODEPACK (ODE solver)EXPAT (XML library)LIBSBML (SBML library)
16 Availability Current Release (June 2006) COPASI Version 4.0 Build 18 COPASI is publicly available since October 2004 (Build 9)
17 Community Integration SBML import and exportBerkeley Madonna exportC source code generation
18 Acknowledgements Mendes group @ VBI Pedro Mendes: Principal Investigator, occasional programmer, tester, and webmasterSameer Tupe: Programmer (Fall Fall 2005)Anurag Srivastava: Programmer (Fall Summer 2005)Christine Lee: Programmer (Fall Spring 2005)Gaurav Singh: Programmer (Fall Spring 2004)Mrinmyee Kulkarni: Programmer (Spring Fall 2003)Liang Xu: Programmer (Spring Fall 2003)Mudita Singhal: Programmer (Spring Summer 2003)Rohan Luktuke: Programmer (Summer Fall 2002)Ankur Gupta: Programmer (Spring 2002 )Wei Sun: Programmer (Fall Summer 2002)Yonqun (Oliver) He: Programmer (Fall Spring 2002)Aejaaz Kamal: Programmer (Spring Summer 2001)Kummer EML ResearchUrsula Kummer: Principal Investigator, testerSven Sahle: Software architect, project manager, programmerRalph Gauges: Software engineering, programmer, documentationJuergen Pahle: ProgrammerNatalia Simus: ProgrammerJürgen Zobeley: TesterUrsula Rost: ProgrammerKatja Wegner: Tester, programmer, documentationRalph Voigt: DocumentationSarah Lilienthal: Programmer (July - August 2005)Wenjun Hu: Programmer (August October 2003)Carel van Gend: Programmer (October May 2002)
19 DOMEDOME is a database and analysis system for functional genomics projects.It can be used to store and analyze transcriptomics, proteomics, and metabolomics data.The analysis that can be performed with DOME allow for an integrated view of the data generated using different technologies.We have implemented the system on three functional genomics projects on Medicago truncatula, Vitis vinifera and Saccharomyces cerevisiae and thus have attempted to make the system general enough to be used by various labs for their functional genomics needs.
20 Overview of DOME Microarray 2D-PAGE Experiment metadata Statistical Analysis- Unsupervised (PCA, clustering)- Supervised (Discriminant analysis, GA-MDA, and others)Visualization- Biochemical Maps(using BROME)Data storageand processingData analysissp_summarySampling_pointSampling_replicatema_normalizedprotein_normalizedmetabolite_normalizedGC/MS; LC/MS; CE/MSgeneproteincompoundeventB-Net
21 Multivariate Data Analysis for Genomics and Systems Biology Current analyses provided:correlation analysispartial correlation analysisprincipal component analysis (PCA), including biplot displaylinear multiple discriminant analysis (MDA),linear multiple discriminant analysis with genetic algorithm variable selection (GA-DFA) - 2 different algorithms.non-negative matrix factorization (NMF)
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