Group meeting in Manchester.

SYSTEMS BIOLOGY

BIOINFORMATICS

ROSTOCKS E Ssimulation experiment management system

Evolution of ComputationalModels in Systems Biologywhat’s the matter – what’s there – what’s next

MARTIN SCHARMDepartment of Systems Biology & Bioinformatics, University of Rostock

http://sems.uni-rostock.de

Research Stay in Manchester, 2015May, 2015 Evolution of Computational Models | Martin Scharm 1

http://www.sbi.uni-rostock.de/team/single/martin-scharm/



SYSTEMS BIOLOGY

BIOINFORMATICS

ROSTOCK

Improving the Management of Simulation Studies in Computational BiologyMartin Scharm, Vivek Garg, Srijana Kayastha, Martin Peters, Dagmar Waltemath

Events

S E Ssimulation experiment management system

https://sems.uni-rostock.de

de.NBI InfrastructureWe will provide data management and support for systems biol-ogy projects, with a focus on provenance and reproducibility ofexperimental and modelling results. de.NBI:SYSBIO is part of alarge German Network for Bioinformatics Infrastructure.WE ARE HIRING!

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p-cyclincdc2-p

p-cyclincdc2

cdc2k

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totalcdc2

SBGN-EDSBGN is a markup language to describe mod-els and exchange information about biological sys-tems graphically. We will further develop meth-ods and tools for SBGN-compliant visualisation ofmodel-related information. WE ARE HIRING!

CombineArchive ToolkitSharing in silico experiments is essential for the advance of researchin computational biology. The COMBINE archive is a digital containerformat to easen the management of numerous files and to enable theexchange of reproducible modelling results. We developed the Combin-eArchive Toolkit, consisting of a library, a web interface and a desktopapplication. It support scientists in creating, exploring, modifying, andsharing COMBINE archives.

2MT2MT is our web based platform todemonstrate the capabilities of SEMS-related tools. It exemplifies how ourmodel management solutions can beused in existing tools.

Models as graphsThe increasing diversity of model-related data that is nec-essary to perform a simulation study leads to new chal-lenges in model storage. We developed a concept forgraph-based storage of models and model-related data.Graphs reflect the models’ structure much better, enablelinking of model-related data on the storage layer, and al-low for an efficient search.

MasymosContaining SBML- and CellML models,linked semantic annotations (e.g., from bio-ontologies), simulation descriptions, graph-ical representations and other availabletypes of model-related data, out graphdatabase Masymos can now be queried forcomplete simulation experiments.

MorreOur retrieval engine for models applies In-formation Retrieval techniques to retrieverelevant models from MASYMOS. The pro-posed ranking and retrieval techniques fo-cus on the processing of model meta-information.

Ontology of DifferencesChanges in model versions are manifoldand appear on different layers. We de-velop an ontology of differences occurring inmodel versions. It will support researchersin analysing differences, discovering typicalchanges, summarising major changes andproviding statistics.

Version Control forComputational Models

With thousands of models available, a framework to track the differencesbetween models and their versions is essential to compare and combinemodels. Focusing on SBML and CellML, we developed an algorithm toaccurately detect and describe differences between versions of a modelwith respect to (i) the models’ encoding, (ii) the structure of biologicalnetworks, and (iii) mathematical expressions.

version x-1 version x version x+1

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G BiVeSArmed with our method for difference detec-tion, BiVeS is able to detect and communicatethe differences in computational models. Thedifferences are exported in several machine-and human-readable formats, ideally suited tobe integrated in other tools.

BudHatBudHat showcases how BiVeS improvesthe understanding of a model’s changes.BudHat calls BiVeS for the comparisontwo versions of a computational model anddisplays the obtained results in the webbrowser.

VW Summer School, March 9-13, 2015During the 2015 Whole Cell summer school we aim todevelop a standard-compliant, open version of the whole-cell model. Eleven tutors and 48 students will hack andcode, model and simulate, layout and annotate the whole-cell model using openly available software and COM-BINE standards. This event is funded by the VolkswagenStiftung.

HARMONY, April 19-23, 2015HARMONY is a hackathon-type meeting of the COMBINE Community,with a focus on development of the standards, interoperability and infras-tructure. Instead of general discussions or oral presentations, the time isdevoted to hands-on hacking and interaction between people focused onpractical development of software and standards. The HARMONY 2015is located at the Leucorea Wittenberg and it is hosted by the groups ofFalk Schreiber and Dagmar Waltemath.

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Workshop on Reproducible and Citable Dataand Models, September 14-16, 2015Computational biologists and experimentalists will learnabout standards, citable data, about how to make scien-tific results sustainable, available through open reposito-ries, and about how to find and reuse other people’s worksin a mixture of lectures and hands-on sessions. The work-shop is funded by the ERASYS-APP program.

Ron Henkel

Dagmar Waltemath

Martin ScharmMartin Peters

Vivek Garg

Srijana Kayastha

-

Ad sponsored by Dagmar Waltemath

Models evolve over time.Example: C. acetobutylicum

metabolic and gene regulation network model in C. acetobutylicum

Haus et. al. 2011

May, 2015 Evolution of Computational Models | Martin Scharm 3



timeinternal Version Release

PapoutsakisEquations and calculations for fermentations of butyric acid bacteria1984 in Biotechnology and bioengineering





Papoutsakis

ShintoKinetic modeling and sensitivity analysis of acetone–butanol–ethanol production2007 in Journal of biotechnology





Papoutsakis

Shinto

COSMIC IA systems biology approach to investigate the effect of pH-induced gene regulationon solvent production by Clostridium acetobutylicum in continuous culture2011 in BMC systems biology





Papoutsakis

Shinto

COSMIC I

COSMIC II

A shift in the dominant phenotype governsthe pH-induced switch in C. acetobutylicum2013 in Applied Microbiology and Biotechnology





Papoutsakis

Shinto

COSMIC I

COSMIC II

???





Papoutsakis

Shinto

COSMIC I

COSMIC II

???

some title20?? in some journal





Papoutsakis

Shinto

COSMIC I

COSMIC II

???





Papoutsakis

Shinto

COSMIC I

COSMIC II

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Model EvolutionCase Study: Cell Cycle

Romond1999 Goldbeter1991 Tyson1991

Novak1993 Marlovits1998

Novak1995Novak1997

Moriya2011

Calzone2007

Novak1998

Tyson2001 Chen2000

Chen2004 Queralt2006 Vinod2011

Novak2001

Sriram2007

Csikasz-Nagy2006

Hatzimanikatis1999

Swat2004

Qu2003Ciliberto2003

mammalian R-point (G1/S-transition)

Srividyha2006

Mitotic exit

Budding Yeast

Not in biomodels database

minimal oscillatorNovak1995

Gardner1998

Ibrahim2008a Ibrahim2008b

Ibrahim2009Mitosis

Obeyesekere1997

Conradie2010

Obeyesekere1999

Bai2003

Aguda&Tang1999

Novak2004

Haberichter2007

(G-Phase)




Romond1999 Goldbeter1991 Tyson1991

Novak1993 Marlovits1998

Novak1995Novak1997

Moriya2011

Calzone2007

Novak1998

Tyson2001 Chen2000

Chen2004 Queralt2006 Vinod2011

Novak2001

Sriram2007

Csikasz-Nagy2006

Hatzimanikatis1999

Swat2004

Qu2003Ciliberto2003

mammalian R-point (G1/S-transition)

Srividyha2006

Mitotic exit

Budding Yeast

Not in biomodels database

minimal oscillatorNovak1995

Gardner1998

Ibrahim2008a Ibrahim2008b

Ibrahim2009Mitosis

Obeyesekere1997

Conradie2010

Obeyesekere1999

Bai2003

Aguda&Tang1999

Novak2004

Haberichter2007

(G-Phase)




CyclinCdc2 P

CyclinCdc2 P

Modeling the cell division...

John J Tyson, 1991

muell




Cyclin

Cdc2 P

Cyclin

Cdc2 P

Cdc25Cdc25∗ Wee1 Wee1∗

Numerical analysis of a comprehensive model of M-phase control in Xenopus oocyte

Bela Novak and John J Tyson, 1993

Cyclin

Cdc2 P

Cyclin

Cdc2 P


John J Tyson, 1991

muell




Cyclin

Cdc2 P

Cyclin

Cdc2 P




Cyclin

Cdc2 P

Cyclin

Cdc2 P

Cdc25Cdc25∗

Mik1 Mik1∗

Wee1 Wee1∗

Quantitative analysis of a molecular model of mitotic control in Fission yeast


Cyclin

Cdc2 P

Cyclin

Cdc2 P


John J Tyson, 1991

muell




Cyclin

Cdc2 P

Cyclin

Cdc2 P




Cyclin

Cdc2 P

Cyclin

Cdc2 P

Cdc25Cdc25∗

Mik1 Mik1∗

Wee1 Wee1∗

Quantitative analysis of a molecular model of mitotic control in Fission yeast


Cyclin

Cdc2 P

Cyclin

Cdc2 P


John J Tyson, 1991

Cyclin

Cdc2 P

Cyclin

Cdc2 P

Cdc25Cdc25∗

Mik1 Mik1∗

Wee1 Wee1∗

Cyclin

Cdc2 P

Rum1

Modeling the control of DNA replication in fission yeast


muell



BiVeSDifference Detection

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RB-Hypo

free E2F

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B

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RB-Hypo

free E2F

cycE/cdk2

RB-Phos

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r

B

C

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A

r

B

C

D

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Biochemical Model Version Control System

• compares models encoded in standadisedformats (currently: and )

• maps hierarchically structured content

• constructs a diff (in XML format)

• is able to interprete this diff

<XML>Diff

movesproduct of r: C

deletesproduct of r: B

insertsspecies: Eproduct of r: Ereaction s

</XML>

mapping

diff construction



BiVeS identifies differencesin versions of computational models

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model version 1model version 2

list of species list of reactions

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pre-

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Identifying, Interpreting, and CommunicatingChanges in XML-encoded Models of BiologicalSystemsScharm et. al. 2015, under revision at BIOINFORMATICS




<?xml version="1.0" encoding="UTF-8" standalone="no"?><bives type="fullDiff">

<update/>

<delete>[...]<node id="6" oldChildNo="1"oldParent="../listOfModifiers[1]"oldPath="../listOfModifiers[1]/modifierSpeciesReference[1]"oldTag="modifierSpeciesReference" triggeredBy="5"/>

<attribute id="7" name="species"

oldPath="../modifierSpeciesReference[1]"oldValue="cdc2" triggeredBy="6"/>

</delete><insert>[...]<node id="12" newChildNo="2"

newParent="../listOfReactants[1]"newPath="../listOfReactants[1]/speciesReference[2]"newTag="speciesReference"/>

<attribute id="13" name="species"

newPath="../speciesReference[2]"newValue="cdc2" triggeredBy="12"/>

<attribute id="14" name="metaid"newPath="../speciesReference[2]"newValue="_818337" triggeredBy="12"/>

</insert>[...]

</bives>

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Scharm et. al. 2015, under revision at BIOINFORMATICS



Indeed!models change over time

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Novak1993 12 updates 20 moves 80 inserts 20 deletes

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Scharm et. al. 2015, under revision at BIOINFORMATICS



COMBINE 2015In Utah

COMBINE 2015: October 12-16 in Salt Lake City

Day 1: invited talks by Fred Adler, Mike Hucka, Richard Normann, SharonCrook, Miriah Meyer, Huaiyu Mi, Tara Deans, and Anil WipatDays 2-5: contributed talks and discussions.

Chris J. Myers (University of Utah) COMBINE 2015 October 12-16

Ad sponsored by COMBINE initiative



Why am I here?The HERMES program

Provenance for models of biological systems

Woche1 2 3 4 5 6 7 8 9 10

Setup / Aligning Visions

Learning & evaluating tools/workflowsIdentifying research gap

Doing a Case StudyDeveloping a concept and a schedule

Start writing a proposalPlanning future



Why am I here?The unofficial goal

Linked DataResearchObjects

Workflows

Networking

SoftwareEngineering

ProjectManagment

BookmakingPro

vena

nce

Proposal

Coordination

Beer



RO vs CAClear the “mess”

Research Object

-vs-

Combine Archive



Comparison of ArchivesMeans to transfer simulation studies

ZIP Docker VBox CombineArchive ResearchObject

Fancy Icon? × Ø Ø Ø Ø

Aspect 2 × × ~ ~ Ø

Aspect 3 × ~ × Ø ~

Aspect 4 × ~ × Ø Ø

Aspect 5 ? ? ? ? ?



RO – CAClear the “mess”

Research Object Combine Archive



Combine ArchiveWhat are already doing.

internet

internet

SEARCHubiquitin

internet

RESULTSEXPORT

EXPORT

EXPORT

EXPORT

Query databasefor annotations, persons,simulation descriptions

Retrieve informationabout models, simulations,figures, documentation

Export simulation studyas COMBINE archive

Download archiveand open the studywith your favouritesimulation tool

Open archive in CATto modify its contents andto share it with others

internet

API Commincationsenrich your studieswith simulation results

Simulate a Studywith just a single click

Extracting reproducible simulation studies from model repositories using the CombineArchive Toolkit.Scharm et. al., DM4LS @ BTW 2015, Hamburg, GER



Research ObjectWhat are already doing.



RO – CAAll singing, all dancing

��♩

��

graphics taken from openclipart.org


https://openclipart.org



Ø What?× Who? When? Why? How? ... ??



Functional Curation ProjectThe WebLab

A call for virtual experiments: Accelerating the scientific process.Cooper et. al., Progress in biophysics and molecular biology (2014).

The Cardiac Electrophysiology Web Lab.Cooper et. al., submitted to Circulation: Arrhythmia and Electrophysiology



Functional Curation ProjectThe WebLab

A call for virtual experiments: Accelerating the scientific process.Cooper et. al., Progress in biophysics and molecular biology (2014).

The Cardiac Electrophysiology Web Lab.Cooper et. al., submitted to Circulation: Arrhythmia and Electrophysiology

Workshop on the Web Lab10th & 11th September 2015Department of Computer Science, University of Oxfordhttp://s.binfalse.de/fcworkshop

Ad sponsored by Jonathan Cooper


http://s.binfalse.de/fcworkshop


SYSTEMS BIOLOGY

BIOINFORMATICS


Thank you!

Dagmar Waltemath, Ron Henkel, Martin Peters, Olaf Wolkenhauer

@SemsProjecthttp://sems.uni-rostock.de

An initiative of:

THE SYSTEMS MEDICINE

WEB HUB

Pictures: Wavebreakmedia Ltd

www.systemsmedicine.net

@sysmednet

sysmednet

The Systems Medicine Web Hub

systemsmedicine.net

www.systemsmedicine.net/feed

SYSTEMSMEDICINE NET

Promote your research

Find jobs and expertsDisseminate your n

ews

Increase your visibility

Be informed

EVENTSREPORTS

RESOURCES

PROJECTSPOSITIONS

Ad sponsored by Olaf Wolkenhauer


https://twitter.com/semsproject



SYSTEMS BIOLOGY

BIOINFORMATICS


References

• Sylvia Haus, Sara Jabbari, Thomas Millat, Holger Janssen, Ralf-Jorg Fischer, Hubert Bahl, JohnKing, Olaf Wolkenhauer: A systems biology approach to investigate the effect of pH-induced generegulation on solvent production by Clostridium acetobutylicum in continuous culture. BMCSystems Biology, 2011, 5:10.

• E.T. Papoutsakis: Equations and calculations for fermentations of butyric acid bacteria.Biotechnology and bioengineering, 1984, 26:174–187.

• H. Shinto, Y. Tashiro, M. Yamashita, G. Kobayashi, T. Sekiguchi, T. Hanai, Y. Kuriya, M. Okamoto,K. Sonomoto: Kinetic modeling and sensitivity analysis of acetone–butanol–ethanol production.Journal of biotechnology, 2007, 131:45–56.

• Thomas Millat, Holger Janssen, Graeme J. Thorn, John R. King, Hubert Bahl, Ralf-Jörg Fischer,Olaf Wolkenhauer: A shift in the dominant phenotype governs the pH-induced metabolic switch ofClostridium acetobutylicumin phosphate-limited continuous cultures. Applied Microbiology andBiotechnology, 2013, 97:6451-6466.

• John J Tyson: Modeling the cell division cycle : cdc2 and cyclin interactions. Proceedings of theNational Academy of Sciences, 1991, 88:7328–7332.



SYSTEMS BIOLOGY

BIOINFORMATICS


• B Novak, J J Tyson: Numerical analysis of a comprehensive model of M-phase control inXenopus oocyte extracts and intact embryos. Journal of Cell Science, 1993, 106:1153-1168.

• Bela Novak, John J. Tyson: Quantitative analysis of a molecular model of mitotic control in fissionyeast. Journal of Theoretical Biology, 1995, 173:283–305.

• B Novak, J J Tyson: Modeling the control of DNA replication in fission yeast. Proceedings of theNational Academy of Sciences of the United States of America, 1997, 94:9147–52.

• M Scharm, O Wolkenhauer, D Waltemath: Identifying, Interpreting, and Communicating Changesin XML-encoded Models of Biological Systems. Under review at BIOINFORMATICS.

• M Scharm, D Waltemath: Extracting reproducible simulation studies from model repositoriesusing the CombineArchive Toolkit. In proceedings of the Workshop on Data Management for LifeSciences (DMforLS 2015) at BTW 2015, Hamburg, GER.

• J Cooper, M Scharm, G Mirams: The Cardiac Electrophysiology Web Lab. Submitted toCirculation: Arrhythmia and Electrophysiology.

• J Cooper, JO Vik, D Waltemath: A call for virtual experiments: Accelerating the scientific process.Progress in biophysics and molecular biology, 2014, 117:1, 99–106.



SYSTEMS BIOLOGY

BIOINFORMATICS


Further Literature

• S Bechhofer, D De Roure, M Gamble, C Goble, I Buchan: Research objects: Towards exchangeand reuse of digital knowledge. In: The Future of the Web for Collaborative Science (FWCS2010); 26 Apr 2010-26 Apr 2010; Raleigh, NC, USA.

• S Bechhofer, I Buchan, D De Roure, P Missier, J Ainsworth, J Bhagat, P Couch, D Cruickshank,M Delderfield, I Dunlop, M Gamble, D Michaelides, S Owen, D Newman, S Sufi, C Goble: Whylinked data is not enough for scientists. Future Generation Computer Systems, 2013, 29(2),599-611.

• FT Bergmann, R Adams, S Moodie, J Cooper, M Glont, M Golebiewski, M Hucka, C Laibe, AKMiller, DP Nickerson, BG Olivier, N Rodriguez, HM Sauro, M Scharm, S Soiland-Reyes, DWaltemath, F Yvon, NL Novère: COMBINE archive and OMEX format: one file to share allinformation to reproduce a modeling project. BMC bioinformatics, 2014, 15(1), 369.



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Group meeting in Manchester.

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