A Tool o Using he SBML Fo ma o Rep esen
P Sys ems which Model Biological Reac ion
Ne wo ks
Isabel Nepomuceno, Juan An onio Nepomuceno,
F ancisco Jos´e Rome o–Campe o
Resea ch G oup on Na u al Compu ing
Depa men o Compu e Science and A i icial In elligence
Uni e si y o Se illa
A da. Reina Me cedes s/n, 41012 Se illa, Spain
E-mail: [email p o ec ed], [email p o ec ed], [email p o ec ed]
Summa y. In his pape we p esen a so wa e ool o ep esen P sys ems modelling
signalling ne wo ks o biochemical eac ions using SBML (Sys ems Biology Ma kup Lan-
guage), a machine- eadable o ma o desc ibing quali a i e and quan i a i e models o
biochemical ne wo ks. CLIPS (C Language In eg a ed P oduc ion Sys em), a ool which
p o ides a comple e en i onmen o he cons uc ion o ule and/o objec based expe
sys ems, has been used o simula ed memb ane sys em. Ou ool ac s as a ansla o
om SBML o CLIPS; ha is, besides p o iding an en i onmen o w i ing SBML code
i also pa ses his code and gene a es au oma ically he CLIPS code ha simula es he
memb ane sys em ep esen ed in SBML.
1 In oduc ion
Memb ane Compu ing is an eme gen b anch o Na u al Compu ing, in oduced by
P˘aun in [9], which conside s he di e en p ocesses aking place in o li ing cells as
compu ing p ocesses. I is a c oss-disciplina y ield, in ol ing Fo mal Languages,
Compu e Science, Cellula Biology, e c; since i s beginning i has ecei ed im-
po an a en ion om he scien i ic communi y and many di e en a ian s om
di e en app oaches and di e en goals ha e been in oduced and s udied. Ac u-
ally, memb ane sys ems ha e been conside ed as a as Eme ging Resea ch F on
in Compu e Science by he Ins i u e o Scien i ic In o ma ion, USA, and [8] was
men ioned in [4] as a highly ci ed pape in Oc obe 2003.
Roughly speaking, a P sys em consis s o a cell-like memb ane s uc u e which
ep esen s he hie a chical s uc u e o he cell, mul ise s o objec s ha a e placed
in he compa men s o he memb ane s uc u e o ep esen chemical subs ances
and e olu ion ules which abs ac he chemical eac ions and p ocesses ha ake
220 I. Nepomuceno, J.A. Nepomuceno, F.J. Rome o-Campe o
place inside he li ing cell. Usually he ules a e applied in a synch onous non-
de e minis ic maximally pa allel manne . Howe e , o he seman ics ha e been p o-
posed, such as a bounded pa allelism, a p obabilis ic applica ion o he ules, an
asynch onous e olu ion o he sys em, e c. Besides, a ian s ha conside a pop-
ula ion o cells (memb ane sys ems) a anged in a g aph ep esen ing a issue like
s uc u e ha e been s udied as well.
Mos a ian s o hese sys ems ha e been p o ed o be compu a ionally com-
ple e, ha is, equi alen in powe o Tu ing machines and compu a ionally e i-
cien , ha is, able o sol e NP-comple e p oblems in polynomial ime by ading
ime o space; o de ails we e e o [10].
Summing up, P sys ems a e a kind o ew i ing sys ems ha mo e a s ep
u he by ep esen ing he hie a chical s uc u e o he li ing cell. Due o he
ac ha his new model o compu a ion is inspi ed by he unc ioning o he cell
i is na u al o s udy and use hese sys ems as a kind o speci ica ion language
and amewo k o he modelling o di e en cellula p ocesses and na u al li ing
sys ems. Se e al a ian s o memb ane sys ems ha e al eady been used o model
biological phenomena (see he olume [2]); ecen ly a con inuous a ian has been
in oduced in [11] and a dynamical p obabilis ic app oach has been s udied in
[1]. These ecen de elopmen s o di e en a ian s used o model biological phe-
nomena inside he amewo k o P sys ems make necessa y in o ma ion s anda ds
o acili a e he po abili y/compa ison o he di e en models in o de o s udy
“when and how” one is be e han he o he .
In his pape we p esen SBML as a con enien machine- eadable o ma o
desc ibing quali a i e and quan i a i e models o biochemical ne wo ks de eloped
wi hin he amewo k o P sys ems. We also p o ide a so wa e ool in ended o be
an en i onmen o w i ing SBML code and a ansla o om SBML o execu able
code. Up o now we ha e only de eloped a ansla o om a SBLM desc ip ion o
a model o CLIPS code simula ing he model using a P sys em.
This pape is o ganized as ollows. In he nex sec ion we b ie ly show how P
sys em ha e been used o model biological phenomena. In Sec ion 3 we desc ibe
SBML, Sys ems Biology Ma kup Language, as a s anda d speci ica ion language
and we discuss some o he cha ac e is ics which make i sui able o ep esen ing
P sys ems. Ou so wa e ool is p esen ed in Sec ion 4; inally, conclusion and
u u e wo k a e gi en in he las sec ion.
2 Modelling Biological P ocesses in he F amewo k o P
Sys ems
Up o now, mos o ma hema ical models o biological p ocesses ha e been based on
using di e en ial equa ions. In his amewo k, he a ia ion o he concen a ion
o each chemical subs ance is modelled as a global p ocess. This app oach makes
di icul he de elopmen o modula and scalable designs. Tha is, in o de o
ex end a p e ious model, one has o s a om sc a ch and ew i e a whole new
Using he SBML Fo ma o Rep esen P Sys ems 221
sys em o di e en ial equa ions. Mo eo e , he modelling o he in e ac ions a
a molecula le el does no scale o he cellula o issue le el. Using memb ane
sys ems we ocus on he memb ane s uc u e and on he local in e ac ions be ween
di e en chemical subs ances, which a e ep esen ed by ules ha a e applicable
in di e en egions. This compu a ional app oach makes possible he ex ension o
p e ious models by simply adding new ules, new objec s and also new memb anes
wi hou making majo changes in he p e ious models. Fu he mo e, ou app oach
is scalable, a e ha ing modelled he in e ac ions a a molecula le el we can s udy
he e olu ion o he sys em as a whole o each he cellula le el and inally, in
o de o ge insigh in o he dynamics a a issue le el we can conside a popula ion
o iden ical sys ems ha ha e been p e iously designed and ha can communica e
h ough he en i onmen o h ough speci ic links.
In his sense he mos impo an cha ac e is ics o ou app oach a e modula i y
and easy ex ensibili y. Beside hese ea u es we men ion easy unde s andabili y and
p og ammabili y o he models de eloped wi hin his amewo k.
Ou wo k has he pape [11] as a s a ed poin . In his pape i was men ioned
he necessi y o in o ma ion s anda ds o acili a e he ci cula ion and s udy o
di e en models, like [1], [2], [7], [11], p oposed o di e en biological phenomena.
SBML was poin ed as a good candida e o achie e his goal. Usual a ian s o
P sys ems a e disc e e models o compu a ion whe e in e e y s ep he ules a e
applied in a maximal way an in ege numbe o imes. A con inuous P sys em
e ol es applying a maximal se o ules a posi i e numbe o imes de e mined by a
ce ain unc ion, see [11]. In o de o implemen /simula e con inuous P sys ems on
eal compu e s we need o de elop app oxima ion me hods which consis basically
in a disc e iza ion o he con inuous e olu ion o he sys ems aking a small in e al
o ime ∆ . In his manne e olu ions o con inuous P sys ems a e app oxima ed
by compu a ions o usual P sys ems wo king in a bounded pa allel manne . Fo
de ails we e e o [11].
The model p esen ed in [11] o modelling EGFR signalling cascade using con-
inuous P sys ems was implemen ed using CLIPS. CLIPS is a an expe sys ems
ool which p o ides a comple e en i onmen o he cons uc ion o he ule and/o
objec based sys ems.
3 SBML: Sys ems Biology Ma kup Language
Ad ances in bio echnology a e leading o la ge , mo e complex quan i a i e models
desc ibing sys ems o biochemical eac ions. The complexi y o hese models is such
ha in o ma ion s anda ds a e necessa y i hese models a e o be sha ed, e al-
ua ed and de eloped coope a i ely. La ely, memb anes sys ems ha e been p o ed
o be a sui able amewo k o de elop local, modula and opological models o
biological p ocesses. These models ha e been designed using di e en a ian s o P
sys ems and hey ha e been implemen ed in di e en P sys ems simula o s w i en
in di e en p og amming languages, like CLIPS, JAVA, PROLOG, e c.
222 I. Nepomuceno, J.A. Nepomuceno, F.J. Rome o-Campe o
SBML, Sys ems Biology Ma kup Language, is a machine- eadable o ma o de-
sc ibing quali a i e and quan i a i e models o biological sys ems, see [14]. SBML
p o ides a s anda d biochemical ne wo k model o ep esen a ion and i p omo es
in e -ope abili y be ween ools. SBML is based on XML, eX ensible Ma kup Lan-
guage, which is a s anda d language o desc ibing ma kups languages. In gene al,
ma kups languages cap u e pa icula in o ma ion in ex o using i : o u u e
p ocessing, o s o ing i , o exchanging i wi h o he sys ems, e c. SBML is s ill
unde de elopmen . Up o now wo le els ha e been eleased. Le el 1 and 2 cap-
u e undamen al ea u es common o all biochemical ne wo k models; he second
le el in a iche manne han he i s one. Le el 3 is abou o be a ailable; i
is de eloped in o de o cap u e se e al aspec s like hie a chical models, spa ial
ea u es, kine ic cons an s, e c.
An SBML documen has he ollowing s uc u e:
<?xml e sion="1.0" encoding="UTF-8"?>
<sbml xmlns="h p://www.sbml.o g/sbml/le el2"
le el ="2" e sion ="1">
<model id = " ">
<lis O Func ionDe ini ions>
...
</lis O Func ionDe ini ions>
<lis O Uni De ini ions>
...
</lis O Uni De ini ions>
<lis O Compa men s>
...
</lis O Compa men s>
<lis O Species>
...
</lis O Species>
<lis O Pa ame e s>
...
</lis O Pa ame e s>
<lis O Rules>
...
<lis O Rules>
<lis O Reac ions>
...
</lis O Reac ions>
<lis O E en s>
...
</lis O E en s>
</model>
</sbml>
Using he SBML Fo ma o Rep esen P Sys ems 223
The ou e mos po ion o an SBML documen consis s o he de ini ion o
Sbml o SBML Le el 2 Ve sion 1. The XML namespace URI o SBML Le el 2
is “h p://www.sbml.o g/sbml/le el2” and he cha ac e encoding o SBML is
UTF-8.
In he nex line an iden i ie is associa ed wi h model and nex he di e en
componen s a e w i en. All hese componen s a e op ional and we will only use
lis O Pa ame e s,lis O Compa men s,lis O Species and lis O Reac ions.
Recall ha a con inuous Psys em is a cons uc , Π= (Σ, µ, w1, . . . , wn,R,K),
whe e:
1. n≥1 is he deg ee o he sys em (numbe o memb anes);
2. Σ={c1, . . . , cm}is he alphabe o objec s;
3. µis a memb ane s uc u e consis ing o nmemb anes labelled wi h 1, . . . , n.
4. w1, . . . , wna e con inuous mul ise s associa ed wi h each memb ane o he
memb ane s uc u e µ
5. Ris a ini e se o ules o he o m:
u[ ]i→u0[ 0]i,
whe e u, , u0, 0∈Σ∗, and 1 ≤i≤n.
6. Kis he a e o applica ion unc ion which associa es wi h each ule and mul-
iplici y o he objec s in µ he a e o applica ion o he ule:
K:R × Mn×m(R+)→R+,
whe e Mn×m(R+) is he se o ma ixes o o de n×mo e R+.
Nex we show how we can speci y P sys ems using SBML.
In he componen lis O Pa ame e s we collec all he unknown pa ame e s
in ou model.
Using he componen lis O Compa men s we can speci y he memb ane
s uc u e ep esen ing he label o he memb ane in he ield id and he hie -
a chical ela ionship be ween he di e en memb anes using he ield ou side.
<lis O Compa men s>
<compa men id= " " ou side= " " >
...
< lis O Compa men s>
The alphabe and ini ial mul ise s o he sys em a e ep esen ed in he compo-
nen lis O Species. Fo each objec in he alphabe we associa e a species wi h
an iden i ie id and in he ields ini ialAmoun and compa men we ep esen
he ini ial mul iplici y and he memb ane whe e he objec is placed in he ini ial
con igu a ion.
<lis O Species>
<species id = " " compa men = " " ini ialAmoun = " ">
...
< lis O Species>

224 I. Nepomuceno, J.A. Nepomuceno, F.J. Rome o-Campe o
A le el 3 we can choose a speci ica ion which allows us o wo k wi h he kind
o eac ions in which we a e in e es ing. We ha e been wo king wi h [3], a p oposal
o speci ica ion o le el 3 which con ains eac ions wi h kine ic cons an s.
Rules ha a e used in [11] a e o he ollowing o m:
u[ ]M−→ u0[ 0]M, KL,
wi h KL he kine ic cons an . We need o exp ess he eac an s and he kine ic
cons an associa ed o he eac ions. Following [3] he co esponding eac ion o
he SBML documen which desc ibes i would be:
< eac ion id=R1 e e sible=" ue">
<lis O Reac an s>
<speciesRe e ence id="u-memb ane_ a he _o _M"
speciesType="u">
<speciesRe e ence id=" -M" speciesType="s">
</lis O Reac an s>
<lis O P oduc s>
<speciesRe e ence id="u’-memb ane_ a he _o _M"
speciesType="u’">
<speciesRe e ence id=" ’-M" speciesType=" ’">
</lis O P oduc s>
<kine icLaw>
<ma h xmlns="h p://www-w3.o g/...">
<apply>
< imes/>
<cn> KL </cn>
<ci> u </ci>
<ci> </ci>
</apply>
</kine icLaw>
</ eac ion>
The main goal o SBML is o p o ide a good desc ip ion o biological p ocesses,
especially biochemical ne wo ks, so machines can ead hem.
4 A Tool o Wo king wi h P Sys ems Modelling Biological
P ocesses
In his pape we p esen a modula ool wi h wo di e en objec i es. In he
i s place, we c ea e a ool wi h a iendly in e ace and a P sys em as engine
made in CLIPS. The engine simula es a conc e e P sys em model in he way we
explained p e iously and his engine is a changeable componen , ha is, he P
sys em implemen ed in CLIPS is changeable wi h o he P sys em implemen ed
Using he SBML Fo ma o Rep esen P Sys ems 225
in CLIPS o in o he language. I has a es ic ion: i o he language is used, he
inpu o ma o his engine mus be in he same o ma as he inpu o ma in
CLIPS. In he second place, he ool ha e a pa se module whose objec i e is o
be able o add ules o he conc e e model ha we like o simula e ( he nex s ep
is o allow o modi y he comple e model wi h i s ules), ha is o say, changing
he engine. In his pa se module he e exis s he possibili y o expo ou model
o a ile which con ains his model in he SBML o ma wi h he objec i e o use
i in o he ool ha accep s he SBML o ma .
The ool is buil as an a chi ec u e model o so wa e de elopmen used in
in e ac i e sys ems. The applica ion, ollowing he MVC (Model-View-Con olle )
a chi ec u e, is composed o h ee di e en componen s. In he i s one, Model
Componen , we ha e he engine o simula o o he EGFR signalling cascade using
con inuous memb ane sys ems made in CLIPS, see [11], he ansla o o models
( om CLIPS o SBML and om SBML o CLIPS), unc ional quali ies and ype
abs ac da a. The second componen , View, has he use guide in e ace espon-
sible o showing he esul s. Finally, he hi d componen , Con olle , es ablishes
he ela ion be ween he engine CLIPS and he Ja a class by means o a dll li-
b a y. Figu e 1 ep esen s he hie a chical s uc u e and he ela ion be ween he
di e en componen s designed in his applica ion.
Logical View
Con olle Componen 
Pa se 
Abs ac Type Da a Engine o Simula o 
GUI Componen 
Model Componen 
Fig. 1. Hie a chical s uc u e and ela ions among he di e en componen s o he appli-
ca ion. We unde line he package (se s o classes) pa se , which con ains all unc ionali ies
o iden i y he SBML o ma and ans o ms i in an inpu ile o he model. The engine
simula o package con ains se e al CLIPS iles. The con olle package con ains lib a ies
o communica e among CLIPS and Ja a.
226 I. Nepomuceno, J.A. Nepomuceno, F.J. Rome o-Campe o
The model p esen ed o simula e he EGFR signalling cascade using con inuous
memb ane sys em has been implemen ing by means o CLIPS. I is a p oduc i e
de elopmen and expe sys em ool which p o ides a comple e en i onmen o
he cons uc ion o ules and/o objec based expe sys em. The engine o he
simula o in CLIPS wo ks independen ly o he es o Ja a package o his ool,
ha is, he CLIPS package is changeable wi h o he model implemen ed in CLIPS.
In his way we can expand ou model and use ye his ool, o example, o model
he PI3K phospho yla ion.
In he Model Componen , see Figu e 1, he e is he pa se package1. A pa se
is a p og am ha akes a se o sen ences as an inpu and inds i s syn ac ic
s uc u e acco ding o a gi en g amma ; hen, he pa se ans o ms his syn ac ic
s uc u e in o he kind o s uc u e ex . This pa se is independen o he model
implemen ed by CLIPS (in his case he EGFR signaling cascade), ha is, we can
use his pa se package o any ype o opological and modula model wo king in
he engine o CLIPS simula o . We ha e implemen ed h ee kinds o pa se s. The
i s one, Pa se ClispToJa a, akes a lis o eac ions w i en in SBML syn ax and
iden i ies he ma kup language o ansla e i , and hen i builds a lis o eac ions
as a lis o ules implemen ed in Ja a. This da a ype is con e ed in he syn ax
used in a inpu ile o a lis o eac ions ha unde s and he model implemen ed in
CLIPS. The second pa se , Pa se SbmlToJa a, is he opposi e o he one abo e;
i ansla es a lis o eac ions w i en in a syn ax used in he CLIPS engine o a
lis o ules implemen ed in Ja a and his is ansla ed o a SBML model. Finally,
we ha e implemen ed a hi d pa se , Pa se EasyRules, o ansla e a simple ule
w i en in he s yle o memb ane compu ing 2, easie o w i e o he use , and
pa ses his in SBML o CLIPS o ma . See Figu e 2 o de ails.
The View Componen includes all classes ha con ain he GUI (Guide Use
In e ace). This is he pa o he p og am which allows he use o in e ac wi h
he applica ion. The Swing Ja a Package is used in he cons uc ion o his GUI.
Finally he Con olle Componen con ains he managemen - ecep ion o e en s
gene a ed be ween he GUI and he simula o engine. In his momen his in e -
ac ion is made only in he di ec ion om he GUI o he engine, ha is, we can
ans o m he o ma o he inpu lis o ules o he model implemen ed and
un he engine CLIPS. The second di ec ion, he p esen a ion o he esul s ( he
e olu ion o a numbe o key p o eins in he EGFR signalling cascade) is unde
de elopmen .
In igu e 3 we p esen he in e ace o he applica ion and we explain how o
use i .
1A package is a g oup o classes whi a simila unc ionali y.
2This easy syn ax o w i e a eac ion is:
u[ ]memb →u0[ 0]membKine iclaw
Using he SBML Fo ma o Rep esen P Sys ems 227
Logical View
Pa se ClispToJa a
+LoadRulesToJa a()
Pa se SbmlToJa a
+LoadRulesToJa a()
Pa se EasyRules
+LoadRulesToJa a()
Rule
-Kine ic : in 
-lis o eac an s : S ing
-Lis o p oduc s : S ing
Ja aToClisp
+T ansla e o Ja a()
Ja aToSbml
+T ansla e o SBML()
Fig. 2. Pa se package: he se o classes. Pa se SBML oJAVA iden i ies and ecognizes
he s uc u e o he sen ences acco ding o a gi en g amma p esen ed in he SBML Le el
3 and build an inpu ile in o ma o be ead by he engine. Pa se ClispToJa a makes
he same in he in e se di ec ion.
5 Conclusions and Fu u e Wo k
In he ollowing e sion o his ool he e will be p esen ed he e olu ion o a
numbe o key p o eins on he signalling ne wo k in a in eg a ed way. We plan
o use he Scien i ic G aphics Toolki (w i en by Donald W. Denbo om he
NOAA/PMEL/EPIC g oup) o c ea ing in e ac i e g aphics applica ions.
In he p esen e sion o ou so wa e, we can in e ac in wo di ec ions: expo -
ing he CLIPS model o SBML o eusing i in o he s ools, and impo ing new
ules in he SBML o ma o add hem o CLIPS model. In a ollowing e sion we
will pe mi no only o impo ules, bu also biological models o new P sys ems
model comple ely.
Re e ences
1. D. Besozzi, G. Mau i, D. Pescini, C. Zand on: Analysis and simula ion o dynamics
in p obabilis ic P sys ems. Submi ed, 2005.
2. G. Ciobanu, Gh. P˘aun, M.J. P´e ez-Jim´enez, eds.: Applica ions o Memb ane Com-
pu ing. Sp inge -Ve lag, Be lin, 2005.
3. A. Finney: Sys ems Biology Ma kup Language (SBML) Le el 3 P oposal:
Mul i-componen Species Fea u es, 2004. A ailable ia he Wo ld Wide Web a :
h p://www.sbml.o g/wo kshops/nin h/supplemen a y/mul i-componen -species.pd
4. ISI web page: h p://esi- opics.com/e /oc obe 2003.h ml
5. JAVA web page: h p://ja a.sun.com
6. I.A. Nepomuceno-Chamo o: A Ja a simula o o memb ane compu ing. J.UCS, 10,
5 (2004), 620–629.