Computational and Systems Biology Course 186— Modeling …Modeling of Biological Systems by...

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Instructor: Van Savage Winter 2017 Quarter Monday and Wednesday, 2-3:50pm 3/15/2017 Computational and Systems Biology Course 186— Modeling of Biological Systems by Connecting Biological Knowledge and Intuition with Mathematics and Computing

Transcript of Computational and Systems Biology Course 186— Modeling …Modeling of Biological Systems by...

Page 1: Computational and Systems Biology Course 186— Modeling …Modeling of Biological Systems by Connecting Biological Knowledge and Intuition with Mathematics and Computing . Fun problem—Pi

Instructor: Van Savage Winter 2017 Quarter

Monday and Wednesday, 2-3:50pm 3/15/2017

Computational and Systems Biology Course 186—

Modeling of Biological Systems by Connecting Biological

Knowledge and Intuition with Mathematics and Computing

Page 2: Computational and Systems Biology Course 186— Modeling …Modeling of Biological Systems by Connecting Biological Knowledge and Intuition with Mathematics and Computing . Fun problem—Pi

Funproblem—PiDay—Buffon’sneedle

What is the probability that a needle of length, L, will cross a line is thrown randomly at a set lines spaced a length, d, apart?

P=2Lπd

Page 3: Computational and Systems Biology Course 186— Modeling …Modeling of Biological Systems by Connecting Biological Knowledge and Intuition with Mathematics and Computing . Fun problem—Pi

Socialorganisms

Page 4: Computational and Systems Biology Course 186— Modeling …Modeling of Biological Systems by Connecting Biological Knowledge and Intuition with Mathematics and Computing . Fun problem—Pi

Socialorganisms

Page 5: Computational and Systems Biology Course 186— Modeling …Modeling of Biological Systems by Connecting Biological Knowledge and Intuition with Mathematics and Computing . Fun problem—Pi

Us

Page 6: Computational and Systems Biology Course 186— Modeling …Modeling of Biological Systems by Connecting Biological Knowledge and Intuition with Mathematics and Computing . Fun problem—Pi

Cancercellsarelikecheatersandhealthycellsinmul?cellularorganisms

arelikecooperators

Page 7: Computational and Systems Biology Course 186— Modeling …Modeling of Biological Systems by Connecting Biological Knowledge and Intuition with Mathematics and Computing . Fun problem—Pi

How do we understand these behaviors, and the complex interplay or altruistic/

generous behaviors and selfish behaviors?

Page 8: Computational and Systems Biology Course 186— Modeling …Modeling of Biological Systems by Connecting Biological Knowledge and Intuition with Mathematics and Computing . Fun problem—Pi

PlatoandAristotle

ForAristotle,altruismshouldalwaysbeaccompaniedbyself-interestedmo?ves.Hissystemofprac?calthoughtcouldbedismissedoutofhandifonebeginswiththeassump?onthatmoralmo?va?onmustbepurelyaltruis?c,freefromalltaintofself-regard.Otherwise,itwouldnotcountasmoral.Thatideahassomecurrency,anditisoJenaKributed(rightlyorwrongly)toKant.Butonreflec?on,itisopentoques?on.Ifitisthecasethatwheneveronehasagoodreasontobenefitsomeoneelseforthatperson’ssake,thereisalsoasecondgoodreasonaswell—namely,thatindoingsoonewillalsobenefitoneself—itwouldbeimplausibletosupposethatoneshouldnotletthatsecondreasonhaveanyinfluenceonone’smo?va?on.RichardKraut,StanfordEncyclopediaofPhilosophy

Page 9: Computational and Systems Biology Course 186— Modeling …Modeling of Biological Systems by Connecting Biological Knowledge and Intuition with Mathematics and Computing . Fun problem—Pi

General Framework— Game Theory as Evolutionary Theory

through Replicator Equations

represents payoff of player i to player j. Benefits are like increases or growth/births and costs like decreases/deaths in biology

Given rules of game, “players” can have different strategies and when different strategies interact, they have different benefits and costs. These interactions and payoffs are described through a payoff matrix that is very similar to our interaction matrix.

π i→ j

Page 10: Computational and Systems Biology Course 186— Modeling …Modeling of Biological Systems by Connecting Biological Knowledge and Intuition with Mathematics and Computing . Fun problem—Pi

Payoffmatrixforinterac?onsamongindividualswithtwodifferent

strategiesAandB

Similartomatriceswe’veseenbefore!Almostallofbiologyorgameisencapsulateinherebycombiningwithevolu?on/growthequa?ons.

Π=π A→A π B→A

π A→B π B→B

⎝⎜⎜

⎠⎟⎟

Selfinterac?ons Cross-strategyinterac?ons

Page 11: Computational and Systems Biology Course 186— Modeling …Modeling of Biological Systems by Connecting Biological Knowledge and Intuition with Mathematics and Computing . Fun problem—Pi

Trajectoriesin?me

Needgrowthequa?onsandexpressthoseintermsofpopula?onsizesofindividualswithstrategyAandthosewithstrategyB.Iftotalpopula?onsizeisN=A+B,thenpA+pB=1wherepA=A/NandpB=B/N.

dpAdt

= pA(?)dpBdt

= pB(?)

Page 12: Computational and Systems Biology Course 186— Modeling …Modeling of Biological Systems by Connecting Biological Knowledge and Intuition with Mathematics and Computing . Fun problem—Pi

Ourfrequencywillincreaseifwearegrowingfasterthanotherstrategyormoregenerallyfasterthanaverage

individualinpopula?onReplicatorEqua?ons

dpAdt

= pA(wA −w)dpBdt

= pB(wB −w)

Mean/averagefitnessacrosspopula?on

meanfitnessofindividualwithstrategyAorB

Page 13: Computational and Systems Biology Course 186— Modeling …Modeling of Biological Systems by Connecting Biological Knowledge and Intuition with Mathematics and Computing . Fun problem—Pi

CalculatemeanfitnessesMeanfitnessofindividualwithstrategyAisprobabilityofinterac?ngwithanotherindividualWithstrategyAandge`ngthatassociatepayoffplustheprobabilityofinterac?ngwithindividualofstrategyBandge`ngthatpayoff.

wA = pAπ A→A + pBπ B→A

SimilarlyforindividualwithstrategyB

wB = pAπ A→B + pBπ B→B

Page 14: Computational and Systems Biology Course 186— Modeling …Modeling of Biological Systems by Connecting Biological Knowledge and Intuition with Mathematics and Computing . Fun problem—Pi

Meanfitnessofen?repopula?on

w = pAwA + pBwb =

pA(pAπ A→A + pBπ B→A)+ pB(pAπ A→B + pBπ B→B )= pA

2π A→A + pB2π B→B + pApB(π B→A +π A→B )

Selfinterac?ons Cross-strategyinterac?ons

Moresimilartohowwereadoffinterac?ontermsandmatricesearlierinclass.

Page 15: Computational and Systems Biology Course 186— Modeling …Modeling of Biological Systems by Connecting Biological Knowledge and Intuition with Mathematics and Computing . Fun problem—Pi

matrixformforreplicatorequa?ons

w =Πp

w =wTp

dpAdtdpAdt

⎜⎜⎜⎜

⎟⎟⎟⎟

= wA −w( ) wB −w( )( ) pApB

⎝⎜⎜

⎠⎟⎟

p=pApB

⎝⎜⎜

⎠⎟⎟

Page 16: Computational and Systems Biology Course 186— Modeling …Modeling of Biological Systems by Connecting Biological Knowledge and Intuition with Mathematics and Computing . Fun problem—Pi

Simplifyequa?onsRightnowequa?onforgrowthofpAappearstodependonpAandpBandwAand.Butisthereawaytosimplify?Anyconstraints?BeKertohavepAgrowthjustintermsofpAandpBgrowthjustintermsofpBandfitnessesjustintermsofdifferencesandra?os.Equa?onsforbuildingbiologicalra?onalearedifferentthanformathema?callysolving.

w

wA −w( ) = (1− pA)(wA −wB )≡ (1− pA)Δw

dpAdt

= pA(1− pA)ΔwpBissameequa?onwithnega?vesignbecauseincreaseForonemeansdecreaseforother.Cangetthisbysubs?tu?ngpA=1-pBorrealizingsignofflips.Reallyonlyoneequa?on!Δw

Page 17: Computational and Systems Biology Course 186— Modeling …Modeling of Biological Systems by Connecting Biological Knowledge and Intuition with Mathematics and Computing . Fun problem—Pi

Biological model for cooperation, mutualism, kin altruism, and Hamilton’s

rule

Page 18: Computational and Systems Biology Course 186— Modeling …Modeling of Biological Systems by Connecting Biological Knowledge and Intuition with Mathematics and Computing . Fun problem—Pi

Aisancooperator/altruistandBisacheaterorfreeloaderoffaltruis?csociety

b–benefitfrommutuallybeneficialinterac?onc–costofgivingbenefitPayoffmatrixis

Π= b− c −c

b 0⎛

⎝⎜⎞

⎠⎟

Page 19: Computational and Systems Biology Course 186— Modeling …Modeling of Biological Systems by Connecting Biological Knowledge and Intuition with Mathematics and Computing . Fun problem—Pi

Δw =wA −wB = −c

Backtoreplicatorequa?ons

dpAdt

= −cpA(1− pA)

Thisisjustlogis?cequa?onagain!

pA(t)=

11+(ect /A0)

Page 20: Computational and Systems Biology Course 186— Modeling …Modeling of Biological Systems by Connecting Biological Knowledge and Intuition with Mathematics and Computing . Fun problem—Pi

Whathappensassystemsevolves

?me

pA(t) pB(t)

Cheaterpopula?ongoestofixa?onandaltruistsgoex?nct,butaltruistshadtoestablishfirstbeforecheaterscouldinvade.Altruistscannotpersists.

Page 21: Computational and Systems Biology Course 186— Modeling …Modeling of Biological Systems by Connecting Biological Knowledge and Intuition with Mathematics and Computing . Fun problem—Pi

Kin altruism and Hamilton

Page 22: Computational and Systems Biology Course 186— Modeling …Modeling of Biological Systems by Connecting Biological Knowledge and Intuition with Mathematics and Computing . Fun problem—Pi

Aisancooperator/altruistandBisacheaterorfreeloaderoffaltruis?csociety

b–benefitfrommutuallybeneficialinterac?onc–costofgivingbenefitr—percentrelatednessofindividualyouinteractwithcanbenefitasdirectindividualorbyindirectbenefitandcosttoageneyoushare.

Π=

b+ r(bi − ci )− c −c + rbib− rci 0

⎝⎜⎜

⎠⎟⎟≡ b'− c ' −c '

b' 0⎛

⎝⎜⎞

⎠⎟

Page 23: Computational and Systems Biology Course 186— Modeling …Modeling of Biological Systems by Connecting Biological Knowledge and Intuition with Mathematics and Computing . Fun problem—Pi

Δw =wA −wB = −c '= −c + rbi

Backtoreplicatorequa?ons

dpAdt

= −c 'pA(1− pA)

Thisisjustlogis?cequa?onagain!

pA(t)=

11+(e(rbi−c )t /A0)

Page 24: Computational and Systems Biology Course 186— Modeling …Modeling of Biological Systems by Connecting Biological Knowledge and Intuition with Mathematics and Computing . Fun problem—Pi

c > rbi

Dynamicsdependonsignofargumentofexponen?al

Cheaterstakeoverwhendirectindividualcostisgreaterthanindirectbenefittorela?on

c > rbiAltruiststakeoverwhendirectindividualcostislessthanindirectbenefittorela?on

c = rbi Altruistsandcheaterscancoexist.

ThisisHamilton’sInequality.FamousresultfromBillHamiltoninthe60’s.

Page 25: Computational and Systems Biology Course 186— Modeling …Modeling of Biological Systems by Connecting Biological Knowledge and Intuition with Mathematics and Computing . Fun problem—Pi

Defaultassump?onofgametheory

Pureselfishnessisassumedtobebasicstate.Makesithardtoexplainpurealtruism.Butwhenflippingitaround,italsohardtoexplainandraretofindpureselfishness.Couldfliparoundaltruismtobedefaultstatebychangingassump?onsandchangingfocus.

Page 26: Computational and Systems Biology Course 186— Modeling …Modeling of Biological Systems by Connecting Biological Knowledge and Intuition with Mathematics and Computing . Fun problem—Pi

Relevantquote"Soonerorlaterinlifewealldiscoverthatperfecthappinessisunrealizable,butfewofuspausetoconsidertheopposite:thatso,too,isperfectunhappiness.Theobstaclespreven?ngtherealiza?onofbothoftheseextremestatesareofthesamenature:theyderivefromourhumancondi?on,whichishos?letoeverythinginfinite.Oureverinadequateknowledgeofthefutureopposesit,andthisiscalled,intheoneinstance,hopeand,intheother,uncertaintyabouttomorrow.Thecertaintyofdeathopposesit,fordeathplacesalimitoneveryjoy,butalsooneverysorrow.Ourinevitablematerialcaresopposeit,for,astheypoisoneverylas?nghappiness,theyjustasassiduouslydistractusfromourmisfortunes,makingourawarenessofthemintermiKentandhencebearable.”--PrimoLevi

Page 27: Computational and Systems Biology Course 186— Modeling …Modeling of Biological Systems by Connecting Biological Knowledge and Intuition with Mathematics and Computing . Fun problem—Pi

Nashequilibriumandevolu?on

JohnNashdevelopedbasicideasofnon-coopera?vegametheory,andwonNobelPriceinEconomics.MademovieABeau?fulMindabouthim.Replicatorequa?onsshownheregivesameresultsthroughdynamicsofevolu?onandsurvivorshipandpersistencewithoutexplicitlyevokingselfishnessorconsciousnessofthat.

Page 28: Computational and Systems Biology Course 186— Modeling …Modeling of Biological Systems by Connecting Biological Knowledge and Intuition with Mathematics and Computing . Fun problem—Pi

Goodreviewandfurtherexplana?onofaltruismandgametheoryin

lecturesbyJeffreySachs

hKp://www.lse.ac.uk/Events/2017/02/20170213t1830vOT/Economics-and-the-Cul?va?on-of-Virtue

Page 29: Computational and Systems Biology Course 186— Modeling …Modeling of Biological Systems by Connecting Biological Knowledge and Intuition with Mathematics and Computing . Fun problem—Pi

Whatismissingfromthismodel?1.  Abilitytocatchandpunishcheaters.Nodirectcosthereto

cheaters.Bigomission.2.  Punishmentmightbe?medelayedfrommostbenefits.

Timedelaysand?mescalesandreallymaKer.3.  Don’thaveabilitytolearn.Ifsomeonecheatsmeonce,I

won’tplaythemagain.“Foolmeonce,shameonyou.Foolmetwice,shameonme.”

4.  Noabilitytochangeandmixstrategiesin?me.5.  Morethantwotypesofstrategies/individuals.6.  No?medelaybetweencostandbenefit.Again,?me

delayscanmaKer.7.  No3-wayorhigher-orderinterac?ons.Justpairwise

effects.

Page 30: Computational and Systems Biology Course 186— Modeling …Modeling of Biological Systems by Connecting Biological Knowledge and Intuition with Mathematics and Computing . Fun problem—Pi

Othertypesofbiological“games”

1.  ChickenorHawk–Dovegame—s?lltwostrategygame.Hawkanddovehaveasharedresource.Dovessplitsresource.Hawksalwaysfightoverresourcesatcosttofightandfullbenefitiftheywin.

2.  Rock-Paper-ScissorsorRochambeau—Non-transi?vegame.Aggression,coopera?on,anddecep?onamonglizardsforwinningmates.Whatdoyouthinkhappensfordynamics?

Page 31: Computational and Systems Biology Course 186— Modeling …Modeling of Biological Systems by Connecting Biological Knowledge and Intuition with Mathematics and Computing . Fun problem—Pi

DynamicsofRochambeau

Flipsbetweenstatessoleadstooscillatorybehaviors.Howwouldwefindthismathema?cally?Itisnowa3equa?onmodel,soevenusingprobabilityconserva?onequa?on,wes?llhave2x2matrix.Needtofindeigenvaluesandusestabilityanalysislikewelearnedearlierintheclass.

Page 32: Computational and Systems Biology Course 186— Modeling …Modeling of Biological Systems by Connecting Biological Knowledge and Intuition with Mathematics and Computing . Fun problem—Pi

Weendclosetowherewebegan,muchlikeanoscilla?onitself.

Page 33: Computational and Systems Biology Course 186— Modeling …Modeling of Biological Systems by Connecting Biological Knowledge and Intuition with Mathematics and Computing . Fun problem—Pi

Talkandreview-  Differen?alequa?onsandgrowth-  Complexity-Stabilityandlinearalgebra(don’tknowif

interac?onmatrixisgenerallyknownoverstandardJacobian)

-  IndirectInterac?onsandhigher-ordereffects-  Modelsforbrain,biochemicalreac?ons,disease

transmission,predator-prey,-  Stochas?csandapplica?ontogenes,cells,species,cancer-  Selfsimilarity,fractals,scaling,andapplica?ontoallometric

biologicalrela?onships,cancer,andsleep-  Networksinbiologyandhowtocluster,iden?fymo?fs,

understanddegreedistribu?onsandpowerlawsandpreferen?alaKachment.

-  Evolu?onofcoopera?on,altruism,andkinselec?onthroughgametheory,replicatorequa?ons,andNashequilibria

Page 34: Computational and Systems Biology Course 186— Modeling …Modeling of Biological Systems by Connecting Biological Knowledge and Intuition with Mathematics and Computing . Fun problem—Pi

Studyguide

Page 35: Computational and Systems Biology Course 186— Modeling …Modeling of Biological Systems by Connecting Biological Knowledge and Intuition with Mathematics and Computing . Fun problem—Pi

Feedbackforfuture

Page 36: Computational and Systems Biology Course 186— Modeling …Modeling of Biological Systems by Connecting Biological Knowledge and Intuition with Mathematics and Computing . Fun problem—Pi

Classevalua?onsthroughmyucla!