BioUML integrated platform for building

virtual cell and virtual physiological human

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Fedor Kolpakov

Institute of Systems Biology

Laboratory of Bioinformatics,Design Technological Institute of Digital Techniques

Novosibirsk, Russia

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;

BioUML workbench http://www.biouml.org/

BioUML web edition

Availabilityhttp://www.server.biouml.org/bioumlweb

BioUML architecture

Plug-in based architecture

Plug-in- plugin.xml

- Java jar files

A plug-in is the smallest unit of BioUML workbench function that can be developed and delivered separately into BioUML workbench. A plug-in is described in an XML manifest file, called plugin.xml. The parsed contents of plug-in manifest files are made available programmatically through a plug-in registry API provided by Eclipse runtime.

- extension points are well-defined function points in the system where other plug-ins can contribute functionality.

- extension is a specific contribution to an extension point. Plug-ins can define their own extension points, so that other plug-ins can integrate tightly with them.

Plug-in - plugin.xml

- Java jar filesPlug-in

- plugin.xml- etc.

Eclipse platform runtime (IBM)

Meta model

Executable model

Graph structure

Standard module

Database

Database adapter

Java objects

Gene Protein …

Diagram types- Semantic map- Pathway- Pathway simulation

Eclipse platform runtime Workbench UI

Diagram editor

Analysistools

Simulation tools

Other tools

Views, editors

Menus, toolbars, etc.

GeneNet module

KEGG/pathwaysmodule

TRANSPATHmodule

SBML module

Perspectives

Diagram view part

Diagram editor part

DiagramType-semantic controller-diagram view builder-diagram filter

ModuleType-diagram types-data categories-query engine

Query engine

BioUML main features• Supports access to main biological databases:

– catalolgs: Ensembl, UniProt, ChEBI, GO…– pathways: KEGG, Reactome, EHMN, BioModels, SABIO-RK,

TRANSPATH, EndoNet, BMOND…• Supports main standards used in systems biology:

SBML, SBGN, CellML, BioPAX, OBO, PSI-MI…• database search:

– full text search using Lucene engine– graph search

• graph layout engine• visual modeling:

– support for hierarchical models;– simulation engine supports (ODE, DAE, hybrid, stochastic, 1D PDE);– parameters fitting;

• genome browser (supports DAS protocol, tracks import/export);• data analyses and workflows – specialized plug-ins for microarray

analysis, integration with R/Bioconductor, JavaScript support, interactive script console.

BioUML web edition

http://server.biouml.org/bioumlweb

Text search

Metaphor: biological systems reconstruction as solitaire (patience) game

Desk – BioUML editor

Solitaire – biological pathway

Cards – biological objects(genes, proteins, lipids, etc.)

Pack of cards – different biological databases

Graph layout

Visual modeling

Pane: model parmaters

Pane: model variables

Pane: model variables

Pane: model simulation

Reports (templates)

Parameters fitting

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

Parameters fitting – usser interface

Comparison with COPASI (10,000 simulations)

Method BioUML

(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 swarm 7,1 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

–

Genome browser

• uses AJAX and HTML5 <canvas> technologies• interactive - dragging, semantic zoom• tracks support

• Ensembl• DAS-servers• user-loaded BED/GFF/Wiggle files

Genome browser: main features

Internet sources

T rack interfaceT rack interface

DAS track

DAS source:UC S C

DAS source:E nsembl

…

E nsembl track

L ocalE nsembl DB S QL T rack (table

in local database)

User-loaded B E D/G F F /Wiggle files

chr1 233604 233639 chr1 559767 559802chr1 742600 742635chr1 742600 742635…

Analys is result:T F B S prediction analys is ,

MAC S analys is , …

C onvert requestedfragment to V iew

S equence interface

…

S equence interface

…C onvert requested fragment to View

S erialize to J S O N and transfer to client (gz ipped)

J S O N-encoded view{"children":[{"children":[{"pen":{"color":[0,0,0,255],"width":1},"height":54,"trackWidth":665,"width":669,"class":"TrackBackgroundView","type":"0","y":10,"x":-2},{"model":"3596179","children":[{"pen":{"color":[0,255,0,255],"width":5},"y1":31,"y2":31,"class":"LineView","x2":664,"type":"0","x1":1},{"alignment":0,"text":"...dust...","font":{"color":[0,0,0,255],"font":["Serif",0,12]},"class":"TextView","type":"0","y":23,"x":313}],"class":"CompositeView","type":"20"},...

Mod

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Deserialize

Draw to <canvas>

T rack view

C ompositeView (s ite)

B oxView(s ite body)

T extView(s ite name)

C ompositeView (s ite)

B oxView(s ite body)

T extView(s ite name)

…

S equence view

C ompositeView (ruler) T extView (sequence)ACGTACGTACGT…

L ineView

L ineView

L ineView

…

View (J ava)T rack view

C ompositeView (s ite)

B oxView(s ite body)

T extView(s ite name)

C ompositeView (s ite)

B oxView(s ite body)

T extView(s ite name)

…

S equence view

C ompositeView (ruler) T extView (sequence)ACGTACGTACGT…

L ineView

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View (J ava)

T rack view

C ompositeView (s ite)

B oxView(s ite body)

T extView(s ite name)

C ompositeView (s ite)

B oxView(s ite body)

T extView(s ite name)

…

S equence view

C ompositeView (ruler) T extView (sequence)ACGTACGTACGT…

L ineView

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View (J avaS cript)T rack view

C ompositeView (s ite)

B oxView(s ite body)

T extView(s ite name)

C ompositeView (s ite)

B oxView(s ite body)

T extView(s ite name)

…

S equence view

C ompositeView (ruler) T extView (sequence)ACGTACGTACGT…

L ineView

L ineView

L ineView

…

View (J avaS cript)

DAS sequenceF ile sequence (F AS T A/E MB L /etc.)

E nsembl sequence

O ther graphical objects like diagrams can be rendered into View and displayed on the web us ing C anvas as well. C reated View can also be used to paint itself on s tandalone client or exported into various raster or vector image formats .

T he same View hierarchy is recreated in client J avaS cript code from J S ON received from the server. If V iew was already created on client, partial updates of changed elements are alsosupported.

Various sequence and track (s ites collection) sources are access ible via unified interfaces making it eas ier to use different data sources .

Poster

WEB-BASED GENOME BROWSERUSING AJAX AND CANVAS TECHNOLOGIES

T.F. Valeev,N.I. Tolstykh, F.A. Kolpakov

Data analyses

R world Java/BioUML world

JavaScript host objects allowsto merge R/Bioconductor and Java/BioUML worlds

Analysis workflow

I.N. Kiselev, A.A. Shadrin,Y.V. Kondrakhin, F.A. Kolpakov

POSTER:MICROARRAY DATA ANALYSIS PLUGIN FOR BIOUML

Virtual physiological human

Virtual physiological humanThe virtual physiological human (VPH) initiative is intended to support the development of patient-specific computer models and their application in personalised and predictive healthcare. The VPH, a core target of the European Commission's 7th Framework Programme, will serve as a ‘methodological and technological framework that, once established, will enable collaborative investigation of the human body as a single complex system' (http://www.europhysiome.org/roadmap/). As such, the VPH initiative constitutes an integral part of the international Physiome Project (http://www.physiome.org.nz/), a worldwide public domain effort to develop a computational framework for the quantitative description of biological processes in living systems across all relevant levels of structural and functional integration, from molecule to organism, including the human (Kohl et al, 2000; Bassingthwaighte et al, 2009).

Kohl P.,Noble D., 2009 (Systems biology and the virtual physiological human. Mol Syst Biol. 2009;

5:292.)

Virtual physiological humansimulation approaches

1. ODE (DAE, hybrid systems)

2. 1D PDEarterial tree, cardio-vascular system

3. Agent based modeling

Models of regulation of blood pressure (Karaaslan et al, 2005)

Numerical analysis of complex model of human blood flow circulation using 1D hemodynamic

modelT.I. Leonova1,2,5,*, E.A. Biberdorf 3,5, F.A. Kolpakov1,2, A.M. Blokhin3, 5, A.L. Markel4.

1Institute of Systems Biology, Novosibirsk, Russia; 2Design Technological Institute of Digital Techniques SB RAS, Novosibirsk, Russia; 3Sobolev Institute of Mathematics SB RAS, Novosibirsk, Russia; 4Institute of Cytology and Genetics SB RAS, Novosibirsk, Russia; 5Novosibirsk State University, Novosibirsk,

Russia.* Corresponding author: : zlove.t@gmail.com

Motivation

High blood pressure – hypertension – is a state affecting hundreds of millions of people worldwide and is a leading cause of morbidity and mortality in developed countries. A complex mathematical model of blood flow circulation has been designed for the purpose of scientific research of human essential hypertension progress.

Tasks and Goals1.Design of one-dimensional (1D) mathematical model of

human vascular system. Adaptation of 1D model to the BioUML workbench for further work.

2.Verification and validation of one-dimensional (1D) model of hemodynamics.

3.Development of a filtration block of the human blood flow circulation model.

4.Development of a closed model of the human blood flow circulation including a filtration block and a model of the heart.

Methods1. The model of the human arterial system was created as a

graph of 55 arteries (Lamponi, 2004 [1]).2.The blood flow in an artery is described by one-

dimensional model. Methods of lines and orthogonal sweep were used for calculations.

3.BioUML (http://www.biouml.org) technology was used for formal description of CVS and development of "Hemodynamics" plug-in that provides user friendly interface for creating model of arterial tree as a graph. The plug-in automatically generates Java or Matlab code for hemodynamics simulation based on this graph.

4.Numerical modeling of an inflatable cuff effect was based on linear and nonlinear functions and has been designed for purposes of validation of the model and researching Korotkoff sounds.

5.Blood flow through the tissue was described by Darcy’s law.

Results

Model of the human arterial system was created on the base of 1D model of blood flow circulation in 55 main arteries using methods of lines and orthogonal sweep. Fig. 1 demonstrates the user interface of BioUML plug-in “Hemodynamics”, which was created for work with 1D model. This model allows simulation of hemodynamics in arterial system with any number of vessels (arterial tree should be binary). Numerical data of blood flow dynamics were obtained for all 55 arteries, as well as for cross-section of arteries according to cardiac contractions. Fig. 2demonstrates pressure dynamics of carotid arteries in comparison with ascending aorta.[2]Numerical model was verified by comparing Euler andRunge-Kutta methods of integrating.

The model was validated on the basis of researching a velocity of the pressure pulse wave. Constructed model of arterial system can reproduce adequately phenomenon of pulse wave.

Numerical modeling of an inflatable cuff effect was based on linear and nonlinear functions and has been designed for purposes of validation of the model and researching Korotkoff sounds. The result of modelling shows that Korotkoff sounds couldn’t be found in a case of circular vessel section.

Model of blood filtration in tissues was created using Darcy’s law on a simple graph of six vessels (Fig. 3, Fig. 4). Fig. 5 a), b) demonstrates pressure dynamics of 1, 2, 5 and 6 vessels in a case of Kf=0.00948 and Kf=0.0948.

Arterial system model was extended by attaching model of vein to the every end artery. Darcy’s law is used to describe blood filtration in tissues (the junction of the artery and vein). The result of modeling shows blood pressure dynamics in all vessels (Fig. 6).

Figure 1. User interface of plug-in “Hemodynamics” in BioUMLworkbench. The vascular tree of 1D model.

Figure 2. Oscillations of blood pressure in ascending aorta (yellow), right carotid, right internal carotid and right external

carotid arteries of hemodynamic tree.

Figure 6. Vessel length-dependent blood pressure dynamics in left leg arteries in t=8.9sec with appended

veins. Kf1=0.00009, Kf2=0.00001.

Figure 5. Time-dependent and vessel length-dependent pressure dynamics in 1, 2, 5 and 6 vessels.

A) Kf=0.00948; B) Kf=0.0948

References1. Daniele N. Lamponi. One dimensional and multiscale models for blood

flow circulation. Pour l'obtention du grade de docteur es sciences. EcolePolytechnique Federale De Lausanne, 2004.

2. Blood circulation system and arterial hypertension: biophysical and genetic-physiological mechanisms, mathematical and computer modeling. Eds. Ivanova L.I., Blokhin A.M., Markel A.L. Novosibirsk: Siberian Branch of Russian Academy of Sciences Press, 2008, 252pp. (Integration projects SB RAS; Issue 17)

AvailabilitySoftware is available as a "Hemodynamics" plug-in for BioUML on website:

http://www.biouml.org/download.shtml?0.8.6/workbench

AcknowledgementsThis work was supported by integration and interdisciplinary grant №91 of

Siberian Branch of Russian Academy of Sciences.

Figure 3. Model of blood filtration in tissues on a graph with six vessels.

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Figure 4. Packing of graph of arterial and vein tree.

Agent based modeling

Agent based modeling

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;

AcknowledgementsPart 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.

Software developers BiologistsNikita Tolstyh Alexey Shadrin Ruslan Sharipov Elena Kutumova Tatyana Leonova Ivan YevshinIlya Kiselev Mikhail Puzanov Tagir Valeev Anna Ryabova