1. BioUML – open source integrated platform for collaborative and reproducible research in systems biology www.biouml.org Fedor Kolpakov, Institute of Systems Biology Ltd. Alexander Kel, geneXplain GmbH

2. 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 scripts (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: BioUML server – provides access to biological databases; BioUML workbench – standalone application. BioUML web edition – web interface based on AJAX technology

4. supported standards: SBML, SBGN, BioPAX, SED-ML, SBO, MIRIAM, CellML – some examples, CellDesigner extension support – state concept – SED-ML as workflow Modular modelling: composite models, agent based models systems biology – reproducible highthroughput data analyses: analyses: algorithms, scripts, workflows integration with R/Bioconductor, Galaxy data: microarrays, NGS, ChIP-SEQ visualization: genome browser BioUML – as platform for collaborative research – Amazon EC2 servers – data repository - groups, projects, import/export, FTP upload – chat, history current works: Biostore, LIMS ( laboratory information management system) Main topics

5. Systems Biology Analysis Computational modeling Experimental data Experimental hypothesis validation

6. Analysis Computational modeling Experimental data Experimental hypothesis validation COMBINE Systems Biology

7. Standard supports: SBML, SBGN, BioPAX, SED-ML, SBO, MIRIAM, CellML

8. import/export - level 1, 2, 3 (core) passed all tests from SBML test suite version 2.0.0 beta 1 (2010, April 2) extensions: – CellDesigner – SBGN-PD (own XML format) Biomodels – full text search – SBGN -PD (parse RDF annotation do determine specie types) – layout algorithms – on-line simulation Panther DB – full text search – reads CellDesigner extensions – SBGN-PD SBML support

13. CellDesigner support – comparison for 165 images from Panther DB and generated by BioUML

14. diagram types: PD – beta; ER, AF – alpha defined as XML graphic notation for BioUML graphic notation can be edited using BioUML graphic notation editor special extension for SBML Reactome - SBGN-PD – full text search – SQL version is used – read diagram layout from Reactome BioPAX – SBGN-PD – level 2 (beta), level 3 (alpha) – auto layout TRANSPATH – SBGN-PD – full text search – auto-layout SBGN support

16. Reactome

17. BioPAX – import dialog

18. BioPAX example (BioCyc)

19. TRANSPATH example

20. SED-ML import – only SBML models are supported now – stored in user’s project SED-ML changes presented as BioUML states SED-ML presented as workflow automated hierarchic layout on-line simulation SED-ML support

21. SED-ML – import dialog

22. SED-ML workflow

23. Simulation

24. Parameters fitting

25. Main features Experimental data – time courses or steady states expressed as exact or relative values of substance concentrations Different optimization methods for analysis Multi-experimentsfitting Constraint optimization Local/global parameters Parameters optimization using java script

26. Parameters fitting – user interface

27. Bentele M, 2004 Neumann L, 2010 CD95L module and results of fitting its dynamics to experimental data

28. Comparison with COPASI (10,000 simulations) MethodBioUML (4 cores) BioUML (1 core) COPASI (1 core) Evolutionary Programming –– 1 min 58,2sec 1 min 31,3 sec 1 min 16,6 sec Particle swarm7,1 sec 7,7 sec 6,9 sec 22,4 sec 15,3 sec 22,5 sec 1 min 32 sec 1 min 26,4 sec 1 min 07,1 sec Stochastic Ranking Evolution Strategy 7,5 sec 7,47 sec 6,9 sec 23,4 sec 23,5 sec 22,2 sec 1 min 25,0 sec 1 min 5,6 sec 1 min 8,8 sec Cellular genetic algorithm 7,7 sec 7,5 sec 7,2 sec 25,5 sec 22,1 sec 20,8 sec –

29. Modular modelling Composite model of the Apoptosis Machinery Agent based model of arterial blood pressure regulation

30. Yuri Lazebnik “Can a biologist fix a radio?—Or, what I learned while studying apoptosis“. Cancer Cell, 2002, 2(3): 179-182

31. Biologist view Engineer’s view

32. 2002 However, I hope that it is only a question of time before a user-friendly and flexible formal language will be taught to biology students, as it is taught to engineers, as a basic requirement for their future studies. My advice to experimental biologists is to be prepared. Y. Lazebnik, 2002 2010 Standards in systems biology SBML – Systems Biology Markup Language SBGN – Systems Biology Graphics Notation

33. TNF-α module (SBGN)

34. Biologist view Engineer’s view

35. Biologist view Engineer’s view Last centaury: 50-70-th

36. Modular design

37. Modules: clear specification of interfaces input/output contacts

38. Modular model of apoptosis 13 modules 286 species 684 reactions 719 parameters

39. EGF module ( BMOND ID: Int_EGF_module) Schoeberl B, et al: Nature Biotechnology 2002 Borisov N, et al: Molecular Systems Biology 2009 Additions: Reactions of protein syntheses and degradations

40. Mitochondron module (BMOND ID: Int_Mitoch_module) Bagci EZ, et al, Biophysical J 2006 Albeck JG, et al, PLoS Biol 2008 Additions: Activation of CREB and deactivation of BAD by Akt- PP and ERK-PP Upregulation of Bcl-2 by CREB Bcl-2 suppression by p53

41. top-down Modular model allows us to combine both up-down and bottom-up approaches bottom-up

42. Computational modeling Experimental data Experimental hypothesis validation COMBINE Systems Biology Data Analysis

43. Systems biology: reproducible highthroughput data analyses – analyses: algorithms, scripts, workflows – integration with R/Bioconductor, Galaxy – data: microarrays, NGS, ChIP-SEQ – visualization: genome browser

45. R world Java/BioUML world JavaScript host objects allows to merge R/Bioconductor and Java/BioUML worlds

47. ChIP-seq processing pipeline

48. Galaxy – analyses methods

49. Galaxy - workflow

50. Genome browser

51. uses AJAX and HTML5 technologies interactive - dragging, semantic zoom tracks support Ensembl DAS-servers user-loaded BED/GFF/Wiggle files Genome browser: main features

54. Computational modeling Experimental data Experimental hypothesis validation COMBINE Systems Biology Data Analysis Data repository for collaborative work

55. BioUML: platform for collaborative research – Amazon EC2 servers – data repository – groups – projects – import/export, FTP upload – chat – history (in process)

58. Main current works: – LIMS (Laboratory Information Management System) – Biostore

59. Computational modeling Experimental data Experimental hypothesis validation COMBINE Systems Biology Data Analysis Data repository for collaborative work LIMS

60. BioUML – LIMS (Laboratory Information Management System) – is being developed by Data Integrated Solutions Inc. (Pittsburg, USA) start-up organized by Maxim Mikheev and Fedor Kolpakov – experiment is represented as workflow – automated management by laboratory equipment – automated generation of tasks for laboratory staff – automated upload of experimental data into repository – automated row data analysis

61. Android market Android AppStore MacOS, iPOD, iPhone Market Platform

62. Android market Android AppStore MacOS, iPOD, iPhone Market Platform Biostore BioUML

63. Biostore BioUML platform Developers - plug-ins: methods, visualization, etc. - databases Users - subscriptions - collaborative & reproducible research Experts -services for data analysis - on-line consultations BioUML ecosystem provide tools and databases use provide services

64. Main platforms for bioinformatics and BioUML Taverna standalone application powerful workflows Galaxy workflows, web interface, collaborative research, genome browser scripts, statistics, plots R/Bioconductor BioUML platform standalone application powerful workflows web interface, collaborative research genome browser scripts, statistics, plots BioClipse Eclipse plug-in based architecture, chemoinformatics Eclipse plug-in based architecture, chemoinformatics

65. Main platforms for bioinformatics and BioUML Taverna standalone application powerful workflows Galaxy workflows, web interface, collaborative research, genome browser scripts, statistics, plots R/Bioconductor BioUML platform standalone application powerful workflows web interface, collaborative research genome browser scripts, statistics, plots + systems biology visual modelling simulation parameters fitting … + chat for on-line consultations BioClipse Eclipse plug-in based architecture, chemoinformatics Eclipse plug-in based architecture, chemoinformatics

66. Acknowledgements Part of this work was partially supported by the grant: European Committee grant №037590 “Net2Drug” European Committee grant №202272 “LipidomicNet” Integration and interdisciplinary grants №16, 91 of SB RAS. BioUML team Software developers Biologists Nikita Tolstyh Ilya Kiselev Ruslan Sharipov Tagir Valeev Elena KutumovaIvan Yevshin Anna Ryabova Alexey Shadrin