Modeling Discrete Interventional Data using Directed Cyclic Graphical Models

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Publié par

pefav

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Langue

English

Poids de l'ouvrage

1 Mo

Modeling Discrete Interventional Data using Directed Cyclic Graphical Models Mark Schmidt and Kevin Murphy Department of Computer Science University of British Columbia June 21, 2009

intracellular multivariate flow

discrete interventional

murphy modeling

introduction interventional

potential model

data using

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Publié par

pefav

Nombre de lectures

Langue

English

Poids de l'ouvrage

1 Mo

Schmidt Murphy

ModelingDiscreteInterventionalDatausing

DirectedCyclicGraphicalModels

MarkSchmidtandKevinMurphy

DepartmentofComputerScience

UniversityofBritishColumbia

June21,2009

siDgniledoMyhpruM.KdnatdimhcS.MnoitubirtnoCruOnoitavitoMstnemirepxEnoitatnemelpmIledoMlaitExperiments

eImplementation

PInterventionalPotentialModel

lIntroduction
Motivation
OurContribution

nOutline

oitnevretnInoitcudortnIsledoMGCDgnisuataDlanoitnevretnIeterc
sledoMGCDgnisuataDlanoitnevretnIetercsiDgniledoMyhpruM.KdnatdimhcS.MnoitubirtnoCruOnoitavitoMstnemirepxEnoitatnemelpmIledoMlaitnetoPlanoitnevretnInoitcudortnIIfI
set
mywatchsoitsays11:55,itdoesn’thelp

IfI
see
thatmywatchsays11:55,thenit’salmostlunchtime

Thediﬀerencebetween
conditioningbyobservation
and
conditioningbyintervention
inthe‘hungryatwork’problem:

collectsbothobservationaland
interventional
data.

collectsalargenumberofsamples

simultaneouslymeasuresmultiplemolecules

Recently,Sachsetal.[2005]analyzedanintracellularmultivariate
ﬂowcytometrydatasetthat:

MotivatingProblem:ModelingBiologicalNetworks

noitubirtnoCruOnoitavitoMstnemirepxEnoitatnemelpmIledoMlaitnetoPlanoitnevretnInoitcudortnIIfI
set
mywatchsoitsays11:55,itdoesn’thelp

IfI
see
thatmywatchsays11:55,thenit’salmostlunchtime

Thediﬀerencebetween
conditioningbyobservation
and
conditioningbyintervention
inthe‘hungryatwork’problem:

collectsbothobservationaland
interventional
data.

collectsalargenumberofsamples

simultaneouslymeasuresmultiplemolecules

Recently,Sachsetal.[2005]analyzedanintracellularmultivariate
ﬂowcytometrydatasetthat:

MotivatingProblem:ModelingBiologicalNetworks

sledoMGCDgnisuataDlanoitnevretnIetercsiDgniledoMyhpruM.KdnatdimhcS.M
sledoMGCDgnisuataDlanoitnevretnIetercsiDgniledoMyhpruM.KdnatdimhcS.MnoitubirtnoCruOnoitavitoMstnemiIfI
set
mywatchsoitsays11:55,itdoesn’thelp

rIfI
see
thatmywatchsays11:55,thenit’salmostlunchtime

eThediﬀerencebetween
conditioningbyobservation
and
conditioningbyintervention
inthe‘hungryatwork’problem:

pcollectsbothobservationaland
interventional
data.

xcollectsalargenumberofsamples

Esimultaneouslymeasuresmultiplemolecules

nRecently,Sachsetal.[2005]analyzedanintracellularmultivariate
ﬂowcytometrydatasetthat:

oMotivatingProblem:ModelingBiologicalNetworks

itatnemelpmIledoMlaitnetoPlanoitnevretnInoitcudortnI
sledoMGCDgnisuataDlanoitnevretnIetercsiDgniledoMyhpruM.KdnatdimhcS.MnoitubirtnoCruOnoitavitoMstnemirepxEnoitatnemelpmIledoMlaitnetoPlanoitnevretnInoitcudortnIIfI
set
mywatchsoitsays11:55,itdoesn’thelp

IfI
see
thatmywatchsays11:55,thenit’salmostlunchtime

Thediﬀerencebetween
conditioningbyobservation
and
conditioningbyintervention
inthe‘hungryatwork’problem:

collectsbothobservationaland
interventional
data.

collectsalargenumberofsamples

simultaneouslymeasuresmultiplemolecules

Recently,Sachsetal.[2005]analyzedanintracellularmultivariate
ﬂowcytometrydatasetthat:

MotivatingProblem:ModelingBiologicalNetworks

noitubirtnoCruOnoitavitoMstnemirepxEnoitatnemelpmIledoMlaitnetoPlanoitnevretnInoitcudortnIsledoMGCDgnisuataDlanoitnevretnIetercsiDgniledoMyhpruM.KdnatdimhcS.MIfI
set
mywatchsoitsays11:55,itdoesn’thelp

IfI
see
thatmywatchsays11:55,thenit’salmostlunchtime

Thediﬀerencebetween
conditioningbyobservation
and
conditioningbyintervention
inthe‘hungryatwork’problem:

collectsbothobservationaland
interventional
data.

collectsalargenumberofsamples

simultaneouslymeasuresmultiplemolecules

Recently,Sachsetal.[2005]analyzedanintracellularmultivariate
ﬂowcytometrydatasetthat:

MotivatingProblem:ModelingBiologicalNetworks

irepxEnoitatnemelpmIledoMlaitnetoPlanoitnevretnInoitcudortnIMotivating

Problem:

Networks

Modeling

Biological

sledoMGCDgnisuataDlanoitnevretnIetercsiDgniledoMyhpruM.KdnatdimhcS.MnoitubirtnoCruOnoitavitoMstnem
noitubirtnoCruOnoitavitoMstnemirepxEnoitatnemelpmIledoMlaitnetoPlanoitnevretnInoitcudortnIsledoMGCDgnisuataDlanoitnevretnIetercsiDgniledoMyhpruM.KdnatdimhcS.MButDAGsdonotallowthemodeltohave
cycles
(mostbiologicalnetworkscontainfeedbackcycles)

DAGscanmodeleﬀectsof
interventions

Wecouldusedirectedacyclicgraphical(DAG)models:

Sowhatkindofgraphicalmodelshouldweuseforthisdata?

Wecoulduseundirectedgraphical(UG)models:

UGsallowthemodeltohave
cycles

ButUGsdonotmodeleﬀectsof
interventions
(thereisnodiﬀerencebetween‘seeing’and‘doing’)

DrawbacksofDirectedAcyclicandUndirectedModels

noitubirtnoCruOnoitavitoMstnemirepxEnoitatnemelpmIledoMlaitnetoPlanoitnevretnInoitcudortnIButDAGsdonotallowthemodeltohave
cycles
(mostbiologicalnetworkscontainfeedbackcycles)

DAGscanmodeleﬀectsof
interventions

Wecouldusedirectedacyclicgraphical(DAG)models:

Sowhatkindofgraphicalmodelshouldweuseforthisdata?

Wecoulduseundirectedgraphical(UG)models:

UGsallowthemodeltohave
cycles

ButUGsdonotmodeleﬀectsof
interventions
(thereisnodiﬀerencebetween‘seeing’and‘doing’)

DrawbacksofDirectedAcyclicandUndirectedModels

sledoMGCDgnisuataDlanoitnevretnIetercsiDgniledoMyhpruM.KdnatdimhcS.M

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