Journal of Integrative Bioinformatics 2006 http://journal.imbio.de/
BASIS: an internet resource for network modelling
Colin S. Gillespie ac, Darren J. Wilkinson ac, Daryl P. Shanley bc, Carole J. Proctor bc,
Richard J. Boys ac, Thomas B.L. Kirkwood bc
aSchool of Mathematics & Statistics, Newcastle University, UK,
bInstitute for Ageing and Health, and SCMS - Gerontology, Newcastle University, UK.
cCentre for Integrated Systems Biology of Ageing and Nutrition, Newcastle University, UK
Summary
There is a growing realisation that complex biological processes cannot be understood
through the application of ever more reductionist experimental programs alone. Recog-
nising this, we have a constructed a flexible web-service based modelling system called
BASIS (Biology of Ageing e-Science Integration and Simulation), which facilitates model
construction and development. In particular it allows users to store, share and simulate their
models. The system is accessed through web-services using any language (e.g. Python or
Java) or under any operating system (e.g. Linux or Windows).
1 Introduction
As a result of recent advances in experimental techniques, biology has become much more of
an informational science. The capacity to answer questions ranging from cell and molecular
function through to the population requires an increasing ability to acquire, store, and manip-
ulate large volumes of raw data in a flexible, efficient manner. Moreover, there is a growing
realization that complex biological processes cannot be understood through the application of
ever-more reductionist experimental programs.
There is a developing perception that mathematical modelling provide some of the necessary
tools required to understand this mass of biological data. Indeed, there are distinct advantages
of modelling a biological process with the rigour needed to build a mathematical model. First,
when constructing a model, gaps in current knowledge are highlighted[14, 25]. Even the very
process of model specification will highlight important unknowns. Second, when building a
model, verbal hypotheses are made specific and conceptually rigorous[2, 6]. Third, models can
yield quantitative as well as qualitative predictions[3, 16].
However, despite the important contributions that are made by models, they are often limited
in their usefulness as they tend not to be easily accessible by those inexperienced in modelling.
For these reasons, we began a project to create a web-service based modelling system known as
the BASIS (Biology of Ageing e-Science Integration and Simulation) system[13]. The primary
objective of BASIS is to help advance the understanding of the complex biology of ageing,
where many different mechanisms act and interact at a range of different levels. However, the
capabilities of BASIS are generic to a wide range of other biological systems. Our system
aims to make both existing and new models accessible to the research community in a way that
users can adapt models and run simulations themselves. We have adopted the Systems Biology
Markup Language (SBML) which is a computer-readable format for representing models of
biochemical reaction networks (see section 2.1 for further details). Currently BASIS is unique

Journal of Integrative Bioinformatics 2006 http://journal.imbio.de/
Cell
S
Binding SE
E
Dissociat ion
Conversion
P
Figure 1: A simple biochemical network.
in that it allows users to interact with advanced modelling facilities through a web service API.
Furthermore, parts of the system can be accessed through a web-browser, or downloaded and
implemented outside of BASIS.
The BASIS project is supported by a team from a wide range of disciplines including biologi-
cal sciences, mathematical and statistical sciences, and computer science. The aim is to bring
the experimental scientists and mathematical modellers into close collaboration, and is already
being realised (see [21] for an example). By sharing and integrating models and data, advances
have been made in our understanding of ageing. BASIS also provides open source download-
able tools in addition to a comprehensive online simulation system and modelling environment
([7] provides details).
2 The system
2.1 Systems biology markup language
In general, the model in the BASIS system can be envisaged as networks of individual biochem-
ical mechanisms, represented by a system of chemical equations, quantified by substrate and
product concentrations and the associated reaction rates. The models can easily be represented
in a standard biochemical diagram (see Figure 1). They are described using SBML[10], which
is essentially an eXtensible Markup Language (XML) encoding of the reaction, species and
compartment lists, together with the additional information required for quantitative modelling
and simulation. SBML is quickly becoming the lingua franca for the development and sharing
of models of biochemical networks[1, 5, 17]. The current version of SBML allows us to encode
and distribute a large class of biochemical network models easily. However there is still a great
deal to add to the SBML specification, for example it is currently difficult to represent tissues
composed of detailed cellular models.
2.2 Web-services
A web-service is a software system designed to facilitate machine to machine interaction over
a network. Messages transmitted between web-services are encoding using SOAP[28]. These

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messages are then usually transmitted using HTTP over port 80. Since the web-service commu-
nicates through the standard web port, this simplifies the configuration of many web-services
since messages can easily pass through fire-walls. Web-service interfaces are described in
the Web Services Description Language (WSDL)[29]. These files describe how web-services
should communicate with each other, and what arguments should be sent/received. SOAP
facilitates the Service-Oriented Architectural(SOA) pattern, that is providing loosely coupled
and highly inter-operable applications. Essentially, since web-services communicate using the
agreed SOAP message system, this enables inter-operability between different languages (e.g.
Java and Python) or different operating systems (e.g. Linux and Windows).
2.3 The BASIS system architecture
The BASIS system of model definition, simulation and visualisation is exposed through several
web-services that are served via Apache (see Figure 2). To provide an initial entry point to the
BASIS system we have constructed a user-friendly web portal for simple model adjustment and
to demonstrate the range of services available (see section 3.1 for further details). The web-
services interact with a postgresql database[19] and the job scheduler, Condor[27]. All details
of the underlying technology are hidden from the user.
To interact with the services that BASIS provides, a user must first register (this is simply
to allow the user to retrieve their models and simulation results). To register with BASIS, a
user can either visit the web-site (https://www.basis.ncl.ac.uk/basis/) or use the web-service
createUser. When registering, a valid email address is required, to discourage potential abuses
of the system.
The majority of the web-services provided by BASIS require a session id as an argument.
A session id is obtained with the getSessionId web-service. As each user logs on, a unique
session id is generated, with each being deleted after one hour of inactivity. In theory users
never deal with the session id, rather the software tool should provide a user-friendly front-end.
For example, the BASIS web-site stores the session id on the client’s web browser as a cookie.
Using the session id, the user can then interact with the BASIS system.
Initially when a user places a SBML model into the BASIS system, the model is designated
private and is only accessible by that user. A user can make their model public (after publication
say). Once a model is public, it can not be deleted.
Every model entered into the BASIS system is assigned a model URN to uniquely identify the
model. The model URN has the form urn:basis.ncl:model:#1 where #1 is an integer.
When a model has been placed into the BASIS system, a user can simulate it using the Gillespie
algorithm. We use a stochastic simulator, which is built using the efficient GNU scientific li-
braries and libSBML. It currently supports local and global parameters, events (without delays),
distributions and assignment rules. The simulator can be downloaded separately and installed
on local machines if required[7]. One of the novel features of BASIS is that when a model
has been simulated using the BASIS system, the results are automatically associated with that
particular model. Therefore, when a model is public, all its associated simulation data is also
public. This allows a pooling of results, i.e. a user can access simulation results from other
users (provided the model is public).

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Figure 2: BASIS Architecture
Access to the simulator on the BASIS system is again via the web-service interface. All simu-
lations are given a urn of the form:
urn:basis.ncl:model:#1:simulation:#2-#3:#3
where #1 is an integer and refers to the model being simulated, #2 is the simulation time, #3 is
the number of time-points to store, #4 is an integer and ensures that the urn is unique and #5 is
an optional number referring to a specific simulation. So for example
urn:basis.ncl:model:401:simulation:100000-1000:418
refers to the simulation of model urn:basis.ncl:model:401, which has been simulated from
t = 0 to 100,000 and outputted at 1,000 iterations.
A user can submit as many simulations as they like. However, at most two of their simulations
will be running at any one time. The other simulations are placed in a queue. In the near
future we plan to join the Newcastle University Grid. This Grid will essentially link all the
unused computing resources in Newcastle University and allow jobs to be scheduled when free
resource time is available.
2.4 Web-service methods
The web-services provided by BASIS can be roughly split into three areas: user, model and
simulation services. The user services deal with the mundane but important matters, such as
logging on/off to BASIS, changing passwords and retrieving a lost password.
The model services allow users to obtain, submit and view SBML models. A few example
services are:
• putSBML(sessionId, sbml)

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– Puts an sbml model into your private space. The model must be valid SBML;
– Returns 1 if successful.
• delSBML(sessionId, modelUrn)
– Deletes the model from the database. If the model is public, then the model will
hidden from view, but still accessible to those that know the modelUrn;
– All simulation data associated with the model is also deleted;
– Returns 1 if successful.
• getMyModelInfo(sessionId)
– Returns information regarding a user’s private model space.
The simulation services deal with submitting a model and retrieving the results. When a model
is private, then all the associated results are private. However, when a model has been made
public, the results are automatically made public. This means that simulations of a particu-
lar public model are also public, allowing users to efficiently combine stochastic simulations.
Example services are:
• simulate(sessionId, modelUrn, runName, maxTime, no of sims, no of iters)
– Sets off a stochastic simulation on the BASIS system;
– The service returns a simulation urn.
• killSimulation(sessionId,simulationUrn)
– Stops a simulation but does not delete the data;
– Returns 1 if successful.
The WSDL file describing all the BASIS web-services is available from
http://www.basis.ncl.ac.uk/basis.wsdl.
3 BASIS in action
3.1 Model building and the BASIS web resources
To provide an initial entry point into the BASIS system we have constructed a user-friendly web
portal interface for simple model adjustment and to demonstrate the range of services available
(see https://www.basis.ncl.ac.uk/basis/). When the user has logged on to BASIS, they are ini-
tially presented with their private model space. From this page, they can add, delete, copy
or simulate an SBML model. Additionally, we have a constructed an online model creation
facility. We do not foresee that users would create large, complicated models online. Instead
we expect users would come to BASIS with a pre-existing model. Their model could be con-
structed using one of the many SBML tools already available (e.g. [24, 26, 23, 4]) or taken
from a SBML model-repository (see [18, 15])

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Rather they can make simple adjustments to their model before simulation. One unexpected
benefit of having a web-site capable of altering models, is that it is now easier to interact with
biologists when model building, since the web-site will run on the majority of current web-
browsers.
3.2 Calling the web-services
In this section a simple use-case for the BASIS web-services will be presented and anal-
ysed. Here a model, mymodel.mod, encoded for discrete stochastic simulation in SBML-
shorthand[30], will be assumed to reside on a client’s local PC. Using the BASIS web-services,
this model will be translated into full SBML, validated, visualised, and submitted to the BA-
SIS model database. Subsequently, a batch of simulation jobs will be requested, and results
will be downloaded to the client’s local PC for detailed analysis. By their very nature, web-
services are language independent. However, for concreteness, the process will be illustrated
using Python[22]. First some relevant python modules need to be imported, and to simplify
subsequent code some appropriate variables are set.
import os, sys, SOAPpy, base64, time
file = ‘mymodel.mod’
wsproxy = ‘http://www.basis.ncl.ac.uk/’
wsproxy += ‘web-services/sbml.py’
bwsproxy = ‘https://www.basis.ncl.ac.uk/’
bwsproxy += ‘web-services/dbServer.py’
uname, passwd = ‘XXXX’, ‘*****’
The variables uname and passwd should be set to a valid BASIS username and password
pair. Note that the generic SBML web-services are un-encrytped and are sent via the default
HTTP port (80), whereas the BASIS-specific web-services are encrytped, and go via the default
HTTPS port (443). Next the SBML-shorthand model is read into a python string.
s = open(file,‘r’)
modstring = s.read()
s.close()
Some generic SBML web-services are now used to convert the SBML-shorthand model to
SBML, validate the model and then produce a graphical representation of the model for local
display.
ws = SOAPpy.SOAPProxy(wsproxy)
sbml = ws.mod2sbml(modstring)
print ws.validate(sbml)
fp = os.popen("xv -", "w")
ws_model = ws.visualiseModel(sbml)
fp.write(base64.decodestring(ws_model))
fp.close()

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Note that the above code assumes a UNIX-like environment and the existence of an image-
viewer called xv. It can be easily modified for other platforms. Now some BASIS-specific
web-services are used to upload the model to the BASIS system and record the URN assigned
to the model by BASIS.
bws = SOAPpy.SOAPProxy(bwsproxy)
sId = bws.getSessionId(uname, passwd)
modURN = bws.putSBML(sId, sbml)
The variable modURN now contains the URN assigned to this model by the BASIS system, and
can be used in subsequent web-service calls for identifying the model. For example, suppose
now that five simulated realisations of the process are required over a period of 100 seconds,
and that the state of the process is required at 1000 time points (every 0.1 seconds). This can
be requested with the following call.
simURN = bws.simulate(sId,modURN,"test runs",str(100),5,1000)
It is important to note that this call returns as soon as the simulation request has been processed
by BASIS. It does not wait until the simulation job has completed. Waiting for job completion
requires some sort of notification mechanism. Unfortunately web-services standards relating to
notification are still in a state of flux. So while it is likely that future versions of the web-services
interface will support more sophisticated notification mechanisms, the current implementation
requires a simple “polling” system to be used to test for job completion. The following piece
of python code illustrates how this can be achieved.
status = bws.getMySimulationGroupInfo(sId, simURN)
while (status[‘jobStatus’] != "f"):
print status[‘jobStatus’], status[‘simulationsCompleted’]
print "Waiting..."
time.sleep(10)
status = bws.getMySimulationGroupInfo(sId, simURN)
print "Job finished!"
Note that data is made available as soon as it has been simulated. So in this example, there is no
requirement to wait for all 5 jobs to finished before analysing the results of (say) the first run. It
should be clear how to modify the above code to return once the first run is complete, if this is
what is required. Once the simulation has completed, the data is available for downloading and
subsequent analysis. For brevity, the following code snippet simply downloads the data for each
model species for each of the 5 independent runs and prints the data to the console. However,
it should be clear how to modify the code to do something more useful with the simulation
results.
species = bws.getMySpeciesInfo(sId,simURN)[‘speciesName’]
for specie in species:
print specie

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for i in range(1,6):
print i
print bws.getMySpecieData(\
sId, simURN+‘:’+str(i), specie)[‘specieValue’]
The example considered in this section is useful for introducing the essential concepts associ-
ated with using the web-services interface, but it is important to understand that more sophis-
ticated interactions are possible. For example, it is very straightforward to use the interface to
carry out a model “parameter scan”, where many simulation jobs are run with varying model
parameter values in order to conduct a sensitivity analysis. The interface can also be used in
the context of parameter inference, where jobs are run with varying parameter values in an
attempt to find parameters which cause the model to behave most like available experimental
data[12]. Indeed this is the whole point of providing a web-services interface. The flexibility
of a programmable interface means that users are free to use the system in ways not necessarily
envisaged by the service providers.
4 Associated tools and resources
There are numerous tools that have been developed as part of the process of building the BASIS
system. Many of these are generic, and have been released as stand-alone tools for the systems
biology community.
1. A Python library (pysbml). This library provides a console based modelling system in
Python, a tool for the visualisation of an SBML model (see Figure 1), and a tool for
converting an SBML model to an HTML file. More information on both installing and
using pysbml can be found in the documentation, available on-line at the BASIS website.
2. A stochastic simulator written in ANSI C (gillespie2). The algorithm executes the stan-
dard Gillespie algorithm[9]. A swig interface has also been provided to allow the simu-
lator to be imported into Python.
3. SBML-shorthand provides a shorthand notation for SBML that is much easier for hu-
mans to read and write than full SBML. The full specification for SBML-shorthand and
a conversion tool is available from the BASIS website.
4. Additionally, a variety of tools have been exposed as web-services, these include model
visualisation (see Figure 1), validation and conversion to an HTML document for display
within a web browser. The WSDL file for these services can be found at
http://www.basis.ncl.ac.uk/sbml.wsdl.
5 Conclusion
The BASIS system is a robust, capable and extensible modelling environment with facilities for
remote storage and simulation of models represented in SBML developed for the research into
ageing community. Many users are currently benefiting from the resources we provide such

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as an actively maintained database of models and simulation results, stochastic simulators and
compute power to release users from tying up their own machines. BASIS is built with web
service technology and is also available to use via a web interface at www.basis.ncl.ac.uk or
for more flexible interaction via our web services. We are currently focusing on a number of
developments that will further the value of BASIS:
1. Simulators. The stochastic simulator has recently been extended to include a suite of ran-
dom distributions which can be accessed by using the CSymbol extension in SBML[8].
The development is essential for modelling telomere shortening[20] but the advantages
extend beyond models of ageing and we are pushing for their inclusion within the SBML
standard. We will soon make available a deterministic simulator on the BASIS system
and we are investigating the inclusion of hybrid simulators as a means to isolate parts of
a large model where stochastic simulation is essential.
2. Web-service technology. Currently, our security is managed using session ids and passing
SOAP messages over a secure socket. In the near future we intend to implement the WS-
Security framework.
3. A BASIS Client. One of the clear advantages of using web service technology is that the
user is free to custom-build a client to interact with the system. We have provided a web
interface which is suitable for minor changes to existing models but not really suitable for
large model development. We have however developed many other tools which connect
to our web services and have been packaged as pySBML[7]. Work is now under way to
provide a fully featured downloadable GUI that embeds these tools within a fully featured
interface.
4. Building large models.
(a) It is highly desirable to build individual models to address specific biological prob-
lems and which can exploit biological modularity. Much can be gained however
in combining these models. In principle this is possible as all models in BASIS
are represented as SBML, but there are a number of problems that must be over-
come. The most obvious is to use a common naming system across models (we are
working on a basic ontology for models relevant to ageing). A conceptually more
difficult problem is to link models not just through common molecular species but
by overloading whole processes with an alternative representation. We are working
towards automating this process.
(b) Multiple instances of component sub models. This is important in modelling a
population of individually encoded mitochondria within a cell, or cells within in a
tissue. There are several proposed SBML extensions that attempt to address this
issue, but none is standard or widely implemented.
We envisage BASIS to be a hub where modellers can not only store their own models and or-
ganise their development but also to further their research value by facilitating model sharing
and integration. BASIS is a valuable addition to the growing range of modelling services which
includes both web-based tools (see [24, 26]) and downloadable software (see [23, 4]). However,
the true power of BASIS will only be realised once it is linked to other web-service enabled
tools such as CaliBayes (www.calibayes.ncl.ac.uk) and KEGG[11], will provide a powerful

Journal of Integrative Bioinformatics 2006 http://journal.imbio.de/
system of interest to both theoretical and experimental biologist alike. The fundamental prob-
lem is that researchers are increasingly having to grapple with complex working models whose
behaviour is difficult to understand from intuition alone. Experimental work to understand
these complex systems must be complemented with in silico experimentation. Furthermore the
increasing cost of experimentation demands that experimental design needs to be optimised.
Enabling technologies such as BASIS are essential to overcome such issues. They are also
needed to provide an environment where effective collaboration can take place, a necessary
requirement for realising the potential of systems biology.
Acknowledgement
This work was funded by BBSRC, MRC, DTI and Unilever plc.
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