1. BioUML – integrated platform for building virtual cell and virtual physiological human Fedor Kolpakov 1,2, Nikita Tolstykh 1,2, Elena Kutumova 1,2, Ilya Kiselev 1,2, Aleksey Shadrin 1,2, Tagir Valeev 1,3, Anna Ryabova 1,3 1 Institute of Systems Biology, Novosibirsk, Russia; 2 Design Technological Institute of Digital Techniques SB RAS, Novosibirsk, Russia 3 A.P. Ershov Institute of Invormatics Systems SB RAS, Novosibirsk, Russia; *Contacts: fedor@biouml.org Motivation Reconstruction of complex biological systems and consequent building of virtual cell and virtual physiological human requires integrated platform that provides: 1.integration with a wide range of biological databases; 2.integration with omics data; 3.powerful search capabilities; 4.decomposition of complex biological systems into blocks and modules; 5.visual modeling, multi-scale modeling, agent based modeling; 6.multi-experiment parameters fitting 7.powerful data analyses capabilities 8.support of reproducible research 9.client-server architecture for team work. Acknowledgements This work was supported by FP6 grant 037590 “Net2Drug”, FP7 grant 090107 "LipidomicNet" and interdisciplinary project 46 of SB RAS. BioUML platform BioUML is an open source integrated platform for systems biology that spans the comprehensive range of capabilities including access to databases with experimental data, tools for formalized description, visual modeling and analyses of complex biological systems. Due to usage of scripting langauges (R, JavaScript) and workflow support it provides powerful possibilities for analyses of high-throughput data. Plug-in based architecture (Eclipse run time from IBM is used) allows to add new functionality using plug-ins. BioUML platform consists from 3 parts: 1.BioUML server - provides access to data and analyses methods installed on the server side for BioUML clients (workbench and web edition) via the Internet. 2.BioUML workbench - Java application that can work standalone or as "thick" client for BioUML server. 3.BioUML web edition - "thin" client for BioUML server (you just need to start web browser) that provides most of functionality of BioUML workbench. It uses AJAX and HTML5 technology for visual modeling and interactive data editing.  supports main standards in systems biology – SBML - Systems Biology Markup Language. BioUML supports SBML Level 1 version 1-2; Level 2 versions 1-4; Level 3 version 1. BioUML is the only simulator that have passed all tests from SBML test suite version 2.0 –SBGN - Systems Biology Graphic Notation. BioUML supports Process Diagrams as they are defined by SBGN version 1.0. –BioPAX - Biological Pathway Exchange. BioUML can import data in BioPAX 2.0 format. Imported data can be stored as native BioPAX file, SQL or text database. –PSI-MI - The Proteomics Standards Initiative Molecular Interaction XML format. –OBO - Ontology Flat File Format. BioUML can import ontology in OBO 1.2 format. Imported data can be presented as semantic networks. –CellML - Cell Markup Language. BioUML can read and simulated biochemical models presented in CellML 1.0 format.  supports main biological databases –catalolgs: Ensembl, UniProt, ChEBI, GO –pathways: KEGG, Reactome, EHMN, BioModels, TRANSPATH, EndoNet, BMOND  powerful search possibilities –full text search (Apache Lucene is used) –graph search - finds related pathway components and presents results as an editable graph  reports, templates –different templates for representing data element info –model reports –Overview –Reactions  Parameters  Variables  ODE(model as differential equation system)  graph layout engine –includes different layout algorithms:  force directed layout  hierarchical layout  cross grid layout  fast grid layout –support incremental graph layout –support compartments –layout preview –possibility to reuse layout for similar diagrams  genome browser –uses AJAX and HTML5 technologies (BioUML web edition) –interactive - dragging, semantic zoom –DAS support (Distributed Annotation System) –tracks support  Ensembl tracks  DAS tracks  user-loaded BED/GFF/Wiggle files  JavaScript support –script console –JavaSsript editor –JavaScript debugger (BioUML workbench only) –JavaScript preprocessor (allows to embed easily R expressions)  R support –connect to R on local or remote machine –convert BioUML data to R and save R results as BioUML data –R graphics support –R preprocessor for JavaScript  SQL support –SQL console –direct SQL access to analysis results tables  visual modeling –powerful diagram editor –virtual experiment - variations of diagram to simulate different experimental conditions, knock-outs, etc. –automated generation of optimized Java code for model simulation from corresponding pathway diagram –different solvers for differential equations:  JVODE - ported to Java version of CVODE  RADAU IIA - (implicit Runge-Kutta method for stiff delay differential equations)  Imex - (implicit Runge-Kutta method for stiff differential equations)  Dormand-Prince - (explicit Runge-Kutta method)  Euler (for debugging complex models) –supports different model types:  ODE - odinary differential equations  DAE - differential algebraic equations  ODE/DAE with delay  1D PDE (for blood flow simulation)  hybrid models support (with events, states and transitions)  hierarchical models –plots (using JFreeChart)  time series  phase portrait  parameters fitting –experimental data - time courses or steady states –experimental data - exact or relative values of substance or concentrations –multiexperiment fitting –global and local parameters for multiexperiment fitting –constraint support –different optimization methods  Adaptive Simulating Annealing  Cellular genetic algorithm  Evolution strategy (SRES)  GLBSOLVE  Particle swarm optimization  Quadratic Hill-climbing –optimization and parallelization of computations –JavaScript API for parameters fitting  data analyses –supports a set of analysis method  biosequence analysis  gene expression regulation modeling  model optimization  statistics –executing analysis from JavaScript  microarray analyses –normalization –annotation –up and down identification –correlation analysis –hypergeometric meta-analysis –cluster analysis  workflow, reproducible research –journal actions  Analysis  JavaScript  SQL requests –allows to present set of actions in research diagram –allows to build and execute workflow document  plug-in based architecture –based on Eclipse runtime –allows to integrate other tools: SBW, R, Matlab, CDK, Lucene,... Main features Availability http://www.biouml.org Mitochondrion module in SBGN notation Genome browser Workflow