Table Of ContentMethods in Cell Biology
VOLUME 110
Computational Methods in Cell Biology
Series Editors
Leslie Wilson
DepartmentofMolecular,CellularandDevelopmentalBiology
UniversityofCalifornia
SantaBarbara,California
Paul Matsudaira
DepartmentofBiologicalSciences
NationalUniversityofSingapore
Singapore
Methods in Cell Biology
VOLUME 110
Computational Methods in Cell Biology
Edited by
Anand R. Asthagiri
DepartmentofChemicalEngineering,NortheasternUniversity,Boston,MA,USA
Adam P. Arkin
DepartmentofBioengineering,UniversityofCalifornia,Berkeley,CA,USA
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CONTRIBUTORS
Numbers in parentheses indicate the pages on which the author’s contributions
begin.
Mark Alber (367), Department of Applied and Computational Mathematics,
University of Notre Dame, Notre Dame, Indiana, USA; Department of
Medicine,IndianaUniversitySchoolofMedicine,Indianapolis,Indiana,USA
Alphan Altinok (285), Division of Biology, California Institute of Technology,
Pasadena,California,USA
AnilAswani(243),DepartmentofElectricalEngineeringandComputerSciences,
UniversityofCalifornia,Berkeley,California,USA
JulioM.Belmonte(325),DepartmentofPhysics,BiocomplexityInstitute,Indiana
University,Bloomington,Indiana,USA
Peter Bickel (243), Department of Statistics, University of California, Berkeley,
California,USA
Mark D. Biggin (243, 263), Genomics Division, Lawrence Berkeley National
Laboratory,Berkeley,California,USA
RichardBonneau(19),DepartmentofBiology,CenterforGenomicsandSystems
Biology, New York University, New York, NY, USA; Computer Science
Department,CourantInstituteofMathematicalSciences,NewYork,NY,USA
Joseph P. Califano (139), Department of Biomedical Engineering, Cornell
University,Ithaca,NewYork,USA
ShawnP.Carey(139),DepartmentofBiomedicalEngineering,CornellUniversity,
Ithaca,NewYork,USA
Scott Christley (367), Department of Surgery, University of Chicago, Chicago,
Illinois,USA
Ann E. Cowan (195), R. D. Berlin Center for Cell Analysis and Modeling,
UniversityofConnecticutHeathCenter,Farmington,CT,USA
Alexandre Cunha (285), Center for Advanced Computing Research, Division of
Engineering andAppliedScience, CaliforniaInstituteofTechnology,Pasadena,
California, USA; Center for Integrative Study of Cell Regulation, California
InstituteofTechnology,Pasadena,California,USA
Hana El-Samad (111), Department of Biochemistry and Biophysics, California
InstituteforQuantitativeBiosciences,UniversityofCalifornia,SanFrancisco,CA
Ernest Fraenkel (57), Department of Biological Engineering, Massachusetts
Institute of Technology, Cambridge, Massachusetts, USA; Computer Science
and Artificial Intelligence Laboratory, Massachusetts Institute of Technology,
Cambridge,Massachusetts,USA
xi
xii Contributors
Ambhighainath Ganesan (1), Department of Biomedical Engineering, Johns
HopkinsUniversity,Baltimore,Maryland,USA
James A. Glazier (325), Department of Physics, BiocomplexityInstitute, Indiana
University,Bloomington,Indiana,USA
Alex Greenfield (19), Computational Biology Program, New York University
SchoolofMedicine,NewYork,NY,USA
CameronHarvey(367),DepartmentofPhysics,UniversityofNotreDame,Notre
Dame,Indiana,USA
Jason M. Haugh (223), Department of Chemical and Biomolecular Engineering,
NorthCarolinaStateUniversity,Raleigh,NorthCarolina,USA
DimitrijHmeljak(325),DepartmentofPhysics,BiocomplexityInstitute,Indiana
University,Bloomington,Indiana,USA
Alexander Hoffmann (81), Signaling Systems Laboratory, San Diego Center for
Systems Biology of Cellular Stress Responses, Program in Bioinformatics and
SystemsBiology,UniversityofCaliforniaSanDiego,LaJolla,California,USA
Shao-shanCarolHuang(57),DepartmentofBiologicalEngineering,Massachusetts
Institute of Technology, Cambridge, Massachusetts, USA; Current address: Plant
MolecularandCellularBiologyLaboratory,SalkInstitutefor BiologicalStudies,
LaJolla,California,USA
Tommy Kaplan (263), Department of Molecular and Cell Biology, California
Institute of Quantitative Biosciences, University of California, Berkeley,
California, USA; School of Computer Science and Engineering, The Hebrew
University,Jerusalem,Israel
Oleg Kim (367), Department of Applied and Computational Mathematics,
UniversityofNotreDame,NotreDame,Indiana,USA
Casey M. Kraning-Rush (139), Department of Biomedical Engineering, Cornell
University,Ithaca,NewYork,USA
Andre Levchenko (1), Department of Biomedical Engineering, Johns Hopkins
University,Baltimore,Maryland,USA
Joshua Lioi (367), Department of Applied and Computational Mathematics and
Statistics,UniversityofNotreDame,NotreDame,Indiana,USA
Leslie M. Loew (195), R. D. Berlin Center for Cell Analysis and Modeling,
UniversityofConnecticutHeathCenter,Farmington,CT,USA
Paul M. Loriaux (81), Signaling Systems Laboratory, San Diego Center for
Systems Biology of Cellular Stress Responses, Program in Bioinformatics and
SystemsBiology,UniversityofCaliforniaSanDiego,LaJolla,California,USA
ElliotM.Meyerowitz(285),DivisionofBiology,CaliforniaInstituteofTechnology,
Pasadena,California,USA
EricMjolsness(285),DepartmentofComputerScience,UniversityofCalifornia,
Irvine,California,USA
IonI.Moraru(195),R.D.BerlinCenterforCellAnalysisandModeling,University
ofConnecticutHeathCenter,Farmington,CT,USA
Contributors xiii
RobertF.Murphy(179),LaneCenterforComputationalBiology,CarnegieMellon
University, Pittsburgh, Pennsylvania, USA; Freiburg Institute for Advanced
Studies,UniversityofFreiburg,Freiburg,Germany
Christopher S. Poultney (19), Department of Biology, Center for Genomics and
SystemsBiology,NewYorkUniversity,NewYork,NY,USA
CynthiaA.Reinhart-King(139),DepartmentofBiomedicalEngineering,Cornell
University,Ithaca,NewYork,USA
Adrienne H.K. Roeder (285), Center for Integrative Study of Cell Regulation,
California Institute of Technology, Pasadena, California, USA; Division of
Biology,CaliforniaInstituteofTechnology,Pasadena,California,USA
Elliot D. Rosen (367), Department of Medical and Molecular Genetics, Indiana
UniversitySchoolofMedicine,Indianapolis,Indiana,USA
James C. Schaff (195), R. D. Berlin Center for Cell Analysis and Modeling,
UniversityofConnecticutHeathCenter,Farmington,CT,USA
AbbasShirinifard(325),DepartmentofPhysics,BiocomplexityInstitute,Indiana
University,Bloomington,Indiana,USA
Boris M. Slepchenko (195), R. D. Berlin Center for Cell Analysis and Modeling,
UniversityofConnecticutHeathCenter,Farmington,CT,USA
Jacob Stewart-Ornstein (111), Department of Biochemistry and Biophysics,
California Institute for Quantitative Biosciences, University of California, San
Francisco,CA
Wenzhao Sun (367), Department of Applied and Computational Mathematics,
UniversityofNotreDame,NotreDame,Indiana,USA
Maciej H. Swat (325), Department of Physics, Biocomplexity Institute, Indiana
University,Bloomington,Indiana,USA
Paul T. Tarr (285), Division of Biology, California Institute of Technology,
Pasadena,California,USA
Gilberto L. Thomas (325), Department of Physics, Biocomplexity Institute,
Indiana University, Bloomington, Indiana, USA; Instituto de F(cid:1)ısica,
UniversidadeFederaldoRioGrandedoSul,C.P.15051,PortoAlegre,Brazil
ClaireTomlin(243),DepartmentofElectricalEngineeringandComputerSciences,
UniversityofCalifornia,Berkeley,California,USA
ErikS.Welf(223),DepartmentofChemicalandBiomolecularEngineering,North
CarolinaStateUniversity,Raleigh,NorthCarolina,USA
Zhiliang Xu (367), Department of Applied and Computational Mathematics,
UniversityofNotreDame,NotreDame,Indiana,USA
PREFACE
Computation is an essential part of the cell biologist’s toolbox. The value of
computationinanalyzingsystemsinvolvingnumerous,interconnectedmechanisms
haslongbeenappreciated.Computationalmodelsprovideaframeworknotonlyto
formallyrepresentandsimulatethemechanisms,butalsopredicttheresponseofan
integrated system to new perturbations and thereby lead to testable hypotheses. In
this way, computational modeling and analysis can suggest new experiments that
challengeandhelpreviseourmechanisticunderstandingofthecellsystem.
Prediction and hypothesis-generation, however, tells only part of the story. The
needforcomputationisnowfarmorepervasiveincellbiology.Cellbiologicaldata
isincreasinglygatheredwithhighbandwidth,oftenexploitingheterotypicmeasure-
ment modalities. This flood of data includes changes in gene expression, post-
translational modifications, and the subcellular location of key regulatory events.
The ‘-omic’scale in vivo imaging of spatiotemporal patterns in gene expression
during the development of model organisms is a compelling example. Extracting
meaningfuldatafromsuchimagesisakeychallengeandinvolvesreliablesegmen-
tation,annotation,storageanddatamanagement,bioinformatics,anddatamining.
Havingacquiredthedata,oneseekstoinfersalientmechanisticrelationshipsand
models.Derivingamodelofhowasystemworksbasedonexperimentaldatais,of
course,notnew.Thechallengenowisthatthevolume,thespatiotemporalresolution,
andtheheterotypicnatureofthedatamakesuchinferencesdifficulttoexecuteby
intuitionalone.Computationalalgorithmstosiftthroughthedataandextractmodels
consistent with the data are essential. Furthermore, model schematics, whether
derivedbycomputationorintuition,areconceptual untiltheyareusedtogenerate
concrete,testablepredictions.Makingsuchpredictions,however,isencumberedby
a dearth of information regarding parameter values and by the fact that cellular
mechanisms often operate over multiple time and spatial scales, in many cases
combiningbiochemicalandmechanicalelements.Thus,inferringcomputablemod-
els that are amenable to simulation requires inference not onlyof the mechanistic
connections,butalsotheparametersthatdescribethestrengthofthoseconnections
andinteractions.
Thisremarkablebreadthofapplicationsofcomputationincellbiologyimpresses
thefactthatcomputationismorethanamoduleinamulti-stepprocessthatinvolves
iterativefeedbackbetweenmodelandexperiment.Itisalsoincreasinglyintegralto
howdataisgatheredandinterpreted,howmechanisticmodelsareinferred,andhow
newmechanismsarehypothesizedanduncovered.Thisvolumecapturesthisbroad
integrationofcomputationinexperimentalcellbiology.Thevolumecoverstherole
ofcomputationintheextractionofquantitativeinformationfromrawdata;inference
xv
xvi Preface
of mechanistic computable (i.e., parameterized) models from large, heterotypic
datasets;andpredictionandhypothesis-generationtodrivenewexperiments.
Thecontributorstothisvolumewerepresentedwithadifficultchallenge:totailor
each chapter in a way that provides both high-level and in-depth tutorials of key
computational methods, while also communicating the biological question that
inspiredthecomputationalapproachandthebiologicalinsightsthatwereuncovered.
The contributors have, in our opinion, succeeded admirably in tackling this chal-
lenge. The chapters are organized into three parts that focus on (1) molecular
regulatory networks, (2) spatial and biophysical aspects of cell regulation, and
finally (3) multicellular systems. Each part of the volume contains chapters that
dealwith the different applications of computation in cell biology: measurements
anddataextraction,modeldevelopmentandinference,andpredictionandhypoth-
esisgeneration.
With acknowledgment and deepest gratitude to the tremendous efforts of the
contributorsandtothemanyanonymouspeer reviewers,wearepleasedtopresent
thisvolumeandtrustthatitwillprovideinspirationandinstructivetutorialinyour
searchfortherightcomputationaltoolforyourcellbiologyquest.
AnandR.Asthagiri
DepartmentofChemicalEngineering,
NortheasternUniversity,Boston,
Massachusetts,USA
AdamP.Arkin
DepartmentofBioengineering,
UniversityofCalifornia,Berkeley,
California,USA
September30,2011
CHAPTER 1
Principles of Model Building: An
Experimentation-Aided Approach to
Development of Models for Signaling
Networks
Ambhighainath Ganesan and Andre Levchenko
DepartmentofBiomedicalEngineering,JohnsHopkinsUniversity,Baltimore,Maryland,USA
Abstract
I. Introduction
II. SignalingSystemsandMathematicalModels
III. Experimentation-aidedModelDevelopment
A. TemplateIdentification
B. ModuleDevelopment
C. ArchitecturalRevision
D. ModelSimulations
IV. Conclusion
Acknowledgments
References
Abstract
Livingcellscontinuouslyprobetheirenvironmentandrespondtoamultitudeof
external cues. The information about the environment is carried by signaling cas-
cades that act as ‘‘internal transducing and computing modules,’’ coupled into
complexandinterconnectednetworks.Acomprehensiveunderstandingofhowcells
makedecisionsthereforenecessitatesasoundtheoreticalframework,whichcanbe
achievedthroughmathematicalmodelingofthesignalingnetworks.Inthischapter,
we conceptually describe the typicalworkflow involved in building mathematical
modelsthat are motivated by and are developed in a tight integration with experi-
mentalanalysis.Inparticular,wedelineatethestepsinvolvedinageneric,iterative
experimentation-driven model-building process, both through informal discussion
METHODSINCELLBIOLOGY,VOL110 0091-679X/10$35.00
Copyright2012,ElsevierInc.Allrightsreserved. 1 DOI10.1016/B978-0-12-388403-9.00001-1