Jianlin Cheng

Institute for Genomics and BioinformaticsSchool of Information and Computer Science

University of California Irvine

Sigmoid: A Systems Biology Infrastructure for the Simulation, Visualization, and Storage of Biological Networks

Biological Networks (Pathways) – Systems Biology

• Modeling networks of molecular reactions

• Metabolic pathways• Signal transduction

pathways • Transcription regulatory

pathways

MAPKinase Pathway

Goals of Sigmoid

Biology

Mathematics

Computing

Hypotheses

•Storage•Simulation•Visualization•Inference

Architecture of Sigmoid

• Four Main Modules • 3-tier Architecture (Model – View –

Controller)

IV. PathwayVisualization

and GUI

I. PathwayRepresentation

StorageDatabase

II. PathwaySimulationInferenceEngine

DatabaseAccess

ModelTranslation

Front End Middle Layer BackendBiologists

III.

Module I: Representation and Storage of Pathway Database

Reactant

BioComplex Molecule

Protein MultimerAffinity Derived

complexAmino Acid Seq DNA RNA Peptide Small Molecule

Known Protein Complex

Y2H Dimer

High Through Put ORF Complex

Lipid

Protein

Hypothetical Protein

Documented Protein

Gene

ORF

Reactant Hierarchy

Reaction Info

BiologicalProcess

Reaction Constraint MetaConstraint Catalysis RateDecorativeActivation

Modification

Pathway BirthProcess DeathProcessElementary

ReactionCompoundReaction

Catalysis

Transcription

creation

Annihilation

Conversion

Elementary biomolecular

Pairwise Protein Association

Diffusion

Decorative Activation

Decomposed Transcription

Pehnomeno LogicalRegtranscription

GRN

Hill

HCAElementary Dissociation

Reaction Hierarchy

Implementation of Biological Pathway Database

• UML (Universal Modeling Language) schema.

• OJB (Object Relation Bridge)• Postgres relational database.• Java

Module II: Simulation Engine

Law of Mass Action

Generate Mathematical Model for Pathway (Cellerator)

Shapiro, BE, Levchenko, A, Meyerowitz, EM, Wold, BJ, and Mjolsness, ED, Bioinformatics

Module III: Distributed and Web-based Computing (Middleware)

• Support distributed, web-based computing and resource sharing.

• Pathway/model objects can be transferred across internet between database, GUI and computation engine via SOAP.

• Java pathway objects need to be translated into mathematica commands recoginized by simulation engine (Cellerator).

Design of Intelligent Middleware

Translate Pathway into Cellerator Commands

GeneratedReaction={List[Overscript[RightArrowLeftArrow[aDHIV,aKIV],DAD],kfDADaDHIV,krDADaDHIVnotsame,kcat$DAD$aDHIV]}

{myODEs, myVars} = interpret[GeneratedReaction]Lamda = 100Omega = 1myKConstants =

{KmDADaDHIV=500;kcat$DAD$aDHIV=1000;kfDADaDHIV->Kf[KmDADaDHIV,kcat$DAD$aDHIV,Lamda],krDADaDHIVnotsame->Kr[kcat$DAD$aDHIV,Lamda]}

myICs = {aDHIV[0]==1000,aKIV[0]==0,DAD[0]==10,$Complex$aDHIV$DAD$[0]== 0}

tmax = 10mySolution =

NDSolve[Join[myODEs/.myKConstants, myICs], myVars, {t, 0, tmax},AccuracyGoal->2, PrecisionGoal->2, MaxSteps->3000]

Plot[aDHIV[t]/.mySolution,{t,0,tmax}, PlotLabel->aDHIV,PlotRange->All]

Plot[aKIV[t]/.mySolution,{t,0,tmax}, PlotLabel->aKIV,PlotRange->All]

aDHIV aKIVDAD(kf,kr)

Module IV: Visualization and GUI

A Simulation Example

AcknowledgementsPierre Baldi

Mike Sweredoski Arlo RandallGianluca Pollastri Alessandro Vullo Hiroto Saigo

Chin-Rang Yang Lucas Scharenbroich Trent SuPeter Hebden

Eric Mjolsness