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www.sys-bio.org www.sbml.org www.sbolstandards.org blog.analogmachine.org. Developing Standards: Case Studies. Herbert M Sauro. Dept. of Bioengineering University of Washington, Seattle, WA hsauro@u.washinton.edu. Importance of Standards. Imagine a world where:

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www.sys-bio.org

www.sbml.org

www.sbolstandards.org

blog.analogmachine.org

Developing Standards:Case Studies

Herbert M Sauro

Dept. of Bioengineering

University of Washington, Seattle, WA

hsauro@u.washinton.edu


Importance of Standards

Imagine a world where:

Each company made its own incompatible nut, bold and screw?

Every town had its own way to measure time.

Every internet provider used different protocols for the ‘TCP/IP’ stack,

email, web etc.

and so on

Standards are vital for the normal functioning of society


At least two ways to start a standard:

1. Top-down: institutionalized stick and carrot

2. Grass Roots


Two Examples

SBML: Systems Biology Markup Language

SBOL: Synthetic Biology Open Language


Simulation of Computational Models

Simulation


Why? Study Perturbations

Apoptosis

Change the activity of a

Protein, e.g. P53 by

adding an inhibitor

http://www.sapphirebioscience.com

What effect does this have on

Cell death and/or proliferation?

There may be multiple paths or multiple effects


How it started:SCAMP and Gepasi: 80/90s

X

SCAMP


Exchange of Computational Models

In 1999/2000 a project was started at Caltech

with initial funding from Japan to devise

an interchange language:

SBML: Systems Biology Markup Language


SBML

SBML: Systems biology Markup Language

Used to represent homogenous

multi-compartmental Biochemical Systems


SBML in a Nutshell“Systems Biology Markup Language”

  • A machine-readableformat for representing computational models in systems biology

  • Domain: systems of biochemical reactions

  • Specified using XML

  • Components in SBML reflect the natural conceptual constructs of the domain

  • Now over 200 tools use SBML


SBML in a Nutshell“Systems Biology Markup Language”

  • Simple Compartments (well stirred reactor)

  • Internal/External Species

  • Reaction Schemes

  • Global Parameters

  • Arbitrary Rate Laws

  • DAEs (ODE + Algebraic functions, Constraints)

  • Physical Units/Model Notes

  • Annotation – extension capability

  • Events


SBML – Systems Biology Markup Language


Model Exchange Standards: SBML, CellML

SBML is primarily a way to describe the biology of

cellular networks from which the mathematical models

can be automatically derived.

CellML is a math based description from which the

underling biological can be inferred.


There many modeling software tools that use SBML

www.sbml.org


SBML

SBML Ecosystem

Unambiguous Model Exchange

Diagrams

Databases

Simulator Comparison and Compliance

Semantic Annotations

Journals

SEDML: Simulation Experiment Description Language

SBGN : Systems Biology Graphical Notation


Model repositories

Nicolas Le Novere

BioModels.net

As of Sep 2011:

366 curated models

398 uncurated models.

http://www.ebi.ac.uk/biomodels/


MIRIAM: Minimum Information Requested in the Annotation of biochemical Models

MIRIAM is not a file format but a minimum specification on how a model should be made available to the community:

Reference correspondence – encoding a model in a

recognized public standardized machine-readable format.

Attribution annotation - A model has to provide the

citation of the reference description, lists its creators,

and be attached to some terms of distribution.

External resource annotation - each component of a model

must be annotated to allow its unambiguous identification.


Semantic Annotations

  • SBO:Systems Biology Ontology (Quantitative terms)

  • 2.MIASE: The Minimum Information About a

    • Simulation Experiment

  • 3.TEDDY: The Terminology for the Description of

    • Dynamics

  • KiSAO: Simulation Algorithm Ontology

  • Missing: An audit trail of a modeling process.


SBO: Systems Biology Ontology

[Term] id: SBO:0000002 name: quantitative parameter def: "A number representing a quantity that defines certain characteristics of systems or functions. A parameter may be part of a calculation, but its value is not determined by the form of the equation itself, and may be arbitrarily assigned." [] relationship: part of SBO:0000000 ! Systems Biology Ontology

[Term] id: SBO:0000012 name: mass action kinetics def: "The Law of Mass Action, first expressed by Waage and Guldberg in 1864 (Waage, P., Guldberg, C. M. Forhandlinger: Videnskabs-Selskabeti Christiana 1864, 35) states that…..." [] is a: SBO:0000001 ! rate law.

Terms can be queried programmatically via a web service


Systems Biology Ontology in SBML

continuous framework

<reaction sboTerm="SBO:0000062">

<listOfReactants>

<speciesReference species="S" sboTerm="SBO:0000015" />

</listOfReactants>

<listOfProducts>

<speciesReference species="P" sboTerm="SBO:0000011" />

</listOfProducts>

<listOfModifiers>

<speciesReference species="E" sboTerm="SBO:0000014" />

</listOfModifiers>

<kineticLaw sboTerm="SBO:0000031">

<listOfParameters>

<parameter id="Km" sboTerm="SBO:0000027" />

<parameter id="kp" sboTerm="SBO:0000025" />

</listOfParameters>

<math xmlns="http://www.w3.org/1998/Math/MathML">

<apply> <divide/> <apply>

<times /> <ci>E</ci>

<ci>kp</ci>

<ci>S</ci>

</apply>

<apply>

<plus /> <ci>Km</ci>

<ci>S</ci>

</apply> </apply> </math> </kineticLaw> </reaction>

substrate

product

enzyme

Briggs-Haldane equation

Michaelis constant

catalytic rate constant

European Bioinformatics Institute


Application: Simulator ComplianceSBML Compliance


The Results


Other Proposed Standards

Standardizing the diagrammatic notation

http://www.sbgn.org/Main_Page


What we all learned


Fact:

Developing a standard has both technical

as well sociological challenges.

The sociological challenges may be greater, :(


Rule #1:

  • There must be a problem (i.e an actual

  • need) that a particular communitywants

  • to solve.

  • Clear scope

  • Covers what is needed

  • Doesn’t force you to deal with things

  • that are not needed


Rule #2:

  • Building a community from day one is

  • of the utmost importance.

  • Build Trust

  • Build Consensus

  • Build Enthusiasm

  • Build Ownership


Rule #3:

  • For a standard to succeed, the central players

  • must provide tools and documentation to help

  • the community use the standard.

  • Easy to implement

  • Low ‘buy in’ cost


Rule #4:

The process is long and drawn out, far beyond

the normal patience of review panels and

funding agencies.


Summary

Initial cost for the SBML development:

Initial version was funded by JST (roughly 250K direct per year for three years). Could probably get by with 150K direct. This funds a core team which is involved in:

1. Documentation

2. Organizing two workshops per year

3. Developing the initial source libraries

4. Develop a governance model

5. Follow discussions on mailing lists/workshops to address

the needs of the community

6. Maintain civility during discussions !


Centralized development of supporting software libraries:

Prevented the standard from diverging

2) As extensions or modifications were agreed to by the community it was relatively easy for platform developers to incorporate the changes into their software.

3) Software developed in C/C++ to make the

library cross-language (Java came later).


Current work of my group: Model Reproducibility

Biology

Data

Simulation Tool

SBML

SEDML

Data

SEDML: What you did

with the model


Synthetic Biology


Synthetic biology

“The design and construction of new biological entities such as enzymes, geneticcircuits, cells, and organsor the redesign of existing biological systems.”

Drew Endy (Stanford)


The Immediate Need

Take any current publication on a synthetic circuit and try to reproduce it, let me know how you get on.


The long term vision: Design, Build, Test

GFP (RFU)

time

Testing/

Analysis

Specification

Design

Build


Synthetic Biology Open Language (SBOL) – SBOL Semantic

Fabricate

SBOL

visual

Synthetic

Biologist A

DNA

Components

B0015

Engineer

Synthetic

Biologist B

81-88

89-129

1-80

DNA

Comp-onent

Sequence Annotation

BioBrick Scar

B0012

B0010

New

device

semantic

Terminator

BioBrick Scar

Terminator

describe and send


Some History

The synthetic biology standardization effort was started with a

grant from Microsoft in 2008 (100K). The first meeting was held

in Seattle.

The first draft proposal was called PoBoL but has since been

renamed to SBOL – Systems Biology Open Language

Since then we have (somehow) managed to organize two

meetings a year since 2008, next one in Jan 2012 in Seattle.


Overall Aim of the Standardization Effort

To support the synthetic biology workflow:

  • Laboratory parts management

  • Simulation/Analysis

  • Design

  • Codon optimization

  • Assembly

  • Repositories - preferably distributed


Overall Aim of the Standardization Effort

Specifically:

  • To allow researches to electronically exchange designs with round-tripping.

  • To send designs to bio-fabrication centers for assembly.

  • To allow storage of designs in repositories and for publication purposes.


Synthetic Biology

Synthetic Biology is Engineering,

i.e it is not biology*

* Beware of sending synthetic biology grant proposals to a biology panel


Synthetic Biology

  • Verification

Synthetic Biology is Engineering,

i.e it is not biology*

Debugging

* Beware of sending synthetic biology grant proposals to a biology panel


Synthetic Biology

  • Verification

Synthetic Biology is Engineering,

i.e it is not biology*

Debugging

* Beware of sending synthetic biology grant proposals to a biology panel


A Real Network (E. coli)

Host Context

Design/Construction

Experimental Data

Increased Repression

Simulation

Increased

Repression

Entus et al, Systems and Synthetic Biology, 2007.

http://www.agricorner.com/e-coli-outbreak-german-farm-in-uelzen-likely-source/


Synthetic Networks

Concentration Detector

Generic Design:

If we control the level of feed-forward

Inhibition we can tune the circuit:


Synthetic Networks

Concentration Detector

Generic Design:

Input: IPTG

Output: GFP


CAD Software- Engineering Cycle

Simulation

Design

Fabrication

Testing


Computational tools and information resources support each step

iBioSim

Clotho

TinkerCell CAD

Public Data

Analysis

Specification

ApE Sequence Editor

BIOFAB

Laboratory Information

GDice

GenoCAD

Design

Build


Registry of Standard Biological Parts (BioBricks)

http://parts.mit.edu

  • Provides free access to an open commons of basic biological functions that can be

  • used to program synthetic biological systems

  • Anybody may contribute, draw upon, or improve the parts maintained within the

    Registry.

Endy D, 2005. Nature 438: 449-453


SBOL is extensible, allows us to form community subgroups

type

SS002

Sample

cell

Experimental Measurements

Computational Models

strain

Cell

MG1655

UW002

dna

subClassOf

type

DNA

Plasmid

pUW4510

B0015

Physical and Host Context

annotation

annotation

annotation

81-88

89-129

1-80

type

Sequence Annotation

Visualization

feature

feature

feature

B0012

B0010

BioBrick Scar

type

type

type

Terminator

BioBrick Scar

Terminator

Assembly Methods

Core SBOL

subClassOf

subClassOf

subClassOf

Sequence Feature


TinkerCell: Project to explore the potential of computer aided design in synthetic biology

First prototype

called Athena

developed

by Bergmann

and Chandran


Layered Architecture: Based on C++/Qt

Octave,


Each component in the TinkerCell diagram is associated with one or more tables


A TinkerCell model can be composed

of sub-models


A TinkerCell model can be composed

of sub-models

?

?

?

?

?

?


Availability

www.tinkercell.com (Windows, Mac and Linux, released under BSD)

Contact author for details (dchandran1@gmail.com)


Challenges in building SBOL

  • Gaining consensus in a growing community

    • Identifying and engaging stakeholders

      • Fast pace of in the field

        • Terminology evolution

      • “BioBricks”  “Parts”  “DNA components”

    • Stability of use cases

      • “Standard” and “Research needs” seem contradictory

    • Software for synthetic biology is new

  • Scarcity of data sources

    • Quality “knowledge” about elements

    • Heterogeneity of existing annotations

  • Funding


http://www.sbolstandard.org/

Who is the we?

University of Washington

Deepak Chandran

John Gennari

Michal Galdzicki

Herbert Sauro

BIOFAB

Cesar Rodriguez

AkshayMaheshwari(now UCSD)

Drew Endy(Stanford)

Joint BioEnergy Institute

Timothy Ham

University of California,

Berkeley

J. Christopher Anderson

University of Utah

Barry Moore

Nicholas Roehner

Chris J. Myers

iBioSim

Boston University

Douglas Densmore

Virginia Bioinformatics Institute

Laura Adam

Matthew Lux

Mandy Wilson

Jean Peccoud

Imperial College of London

Guy-Bart Stan

Newcastle University (UK)

Aniel

Recent Commercial Interest

BBN, DNA 2.0, Agilent

Life Technologies, AutoDesk

University of Toronto

Raik Gruenberg


Hamid Bolouri

Andrew Finney

Mike Hucka

Herbert Sauro

Frank Bergmann

Deepak Chandran

Vijay Chickarmane

Michal Galdzicki

Lucian Smith

Acknowledgements: The People and the Support

Funding in chronological order(2000 -> 2011):

……


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  • 318 pages, 94 illustrations and 75 exercises

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  • Author: H M Sauro


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