SBML Viewer: A graphical displayer for SBML

Transcription

1 SBML Viewer: A graphical displayer for SBML Laurent Francioli Laurent.francioli@epfl.ch Under the supervision of Jean-Yves Le Boudec jean-yves.leboudec@epfl.ch Semester Project at the LCA as part of the Simulation of the Immune System Project Swiss Institute of Technology, 1015 Lausanne, Switzerland February 19 th, 2006 Abstract Networks of biological interactions are often very complex due to large number of actors, complicated interactions between them and probabilistic transitions between states. SBML Viewer is a java application to display and work on biological networks in the Systems Biology Markup Language (SBML) format [1, 4]. Introduction A biological network is a set of reactions forming a network and describing a biological system. They are used to model and study interactions between biological entities in very different contexts from food chain webs to biochemical reactions and cell interactions. The reactions composing the biological network describe the connections between the different entities of the model. There are different approaches to extract information from such networks; our group focuses on a simulation approach. It is a promising topic of research since it could lead to great medical applications such as in-silico drug testing, understanding patterns of biological reactions, testing hypothesis on biological pathways, etc. SBML Viewer is a java application belonging to a simulation framework. It aims to give a graphical representation of such networks and provide tools to set them up for simulation. Simulation of Biological Networks Framework Our group recently began a project in collaboration with the Centre Hospitalier Universitaire Vaudois (CHUV) to help develop a model and a simulator of the T-cell response in the immune system. More precisely, the goal of this work is to simulate experiments in collaboration with the immunology research group at CHUV. The first step of this project is to build a framework to describe, represent and simulate networks of biological interactions. It will then be used as a research and communication platform to model and simulate different biological networks and compare them with invitro results obtained at the CHUV. SBML Viewer is part of this framework and its purpose is to graphically represent the biological networks and set them up for simulation. Framework Design Choices We decided to build our framework using Java to have a platform independent code. The choice of Java also came from the different libraries available for this language; the libraries used for SBML Viewer are detailed in Design Choices chapter.

2 The whole framework uses SBML as an exchange format; this was a natural choice since SBML is becoming a standard in software for biological data analysis. The choice of SBML also insures that other applications can communicate with our framework through SBML. The framework comports 4 parts: A textual representation compiler realized by M.Sede [2] A SBML compiler to MathLab for simulation realized by J.Eperon [3] A SBML compiler to LaTeX realized by J.Eperon [3] And the graphical representation tool described in this paper: SBML Viewer Representation of Biological Networks Representation of biological networks is determinant to design valuable models in our project because it involves research groups from different backgrounds. The biologists at CHUV have the biological knowledge while the computer scientists at EPFL will realize the simulations themselves. Because the knowledge is split among the groups, the representation of the model serves as a basis to transfer the information from one group to the other. The representation must therefore be simple, precise and unambiguous. Our group decided to provide two different representations to model the biological networks: a text representation and a graphical representation. Standard Chemical Representation We took as a basis to clearly represent the reactions composing the biological networks, the standard representation used to describe chemical reactions: Reactants rate Products With: The Reactants entity being the set of all species of the reactions been consumed. The Reactants is always on the tail side of the arrow. The Products entity being the set of all species of the reactions been created. The Products is always on the head side of the arrow. Any element of these sets has a certain stoichiometry. If an element is used for a reaction but isn t consumed, it then appears on both sides of the reaction. The rate defines the rate at which the reaction takes place. The direction of the arrow indicates the direction of the reaction; it can either be unidirectional or bidirectional. When a bidirectional arrow is used, both sides can be either Reactants or Products depending on the instance of the reaction. This standard notation will be used through this paper to describe biological reactions. We chose this as a basis since it s been widely used and proved to be clear and efficient. Unfortunately, it wasn t fully sufficient to be used directly for our simulation for the following reasons: It couldn t be compiled in order to be read and simulated; the textual representation [2] addressed this problem. It doesn t provide a global view of the network and therefore complex systems are unreadable by humans; SBML Viewer has therefore been developed to give a better global view on the system. Textual Representation The text representation has been developed by M. Sede and is thoroughly explained in [2]. M. Sede also developed a compiler to transform this textual representation in SBML, our standard communication format. Graphical Representation As explained earlier, the standard chemical representation is not sufficient to give a global view of a complex system. The graphical representation I developed aims to give the user both a local and a global view of the system. It contains the same information as the textual representation and shows it in an unambiguous way. Since SBML Viewer is designed to follow the SBML format, it also respects the format constraints of SBML [4]. A network is represented using only 2 entities Species and Reactions - and 1 connection type - a unidirectional arrow -, which makes the graph clear and easily readable.

3 The species and reactions have names in order to designate them; these names are unique within the graph to avoid naming ambiguities. The names also have to respect the SBML naming format [4]. A species is an actor of the biological network. They are represented as a green square and are labelled with the species name, as shown in Figure 1: Species RepresentationFigure 1. Figure 1: Species Representation A Species can be reactants and/or products in any number of reactions. A reaction is represented using an orange ellipse with arrows pointing from its reactant species and arrows pointing to its products species. The reactions are labelled using the format: name, rate. For example, the Figure 2 shows the reaction named Reaction_Name corresponding to: Reactant1 + Reactant2 rate Product Figure 3: Connection with stoichiometry As specified earlier, the connections can only be unidirectional. This choice has been made in order to discard any ambiguity; if a species is both a reactant and a product for a certain reaction then two arrows will be created in order to permit different stoichiometries for the species as a reactant and a product. Another consequence from this design is that all the bidirectional reactions have to be split in two different reactions to be displayed. For example the reaction: A + B rate C Will be split into: A + B rate C A + B rate C Figure 4 shows the above reaction graphed with bidirectional arrows: Figure 2: Reaction Representation Reactions connect 0 or more reactants to 0 or more products. If there are no reactants, it indicates the apparition of a species with a certain rate. If there are no products, it indicates the death of a species with a certain rate. A connection is represented with an arrow linking a Species to a Reaction. The head of the arrows determines whether the Species is a Reactant (head of the arrow on the Reaction side) or a Product (head of the arrow on the Species side). The connections have the stoichiometry of the species for the reaction as a label. If the stoichiometry equals 1, there won t be any label in order to keep the graph as clean as possible. The Figure 3 shows the following reaction where the species Species_Name has a stoichiometry of 3: 3 Species_Name Ø Figure 4: ambiguous reaction The graph showed in Figure 4 is ambiguous since it cannot be told if the reaction modelled is: A + B rate C A + C rate B B + C rate A A + B rate A + C When modelling the same reaction using two reactions, the graph of the figure 5 is obtained. Figure 5: Unambiguous reaction

4 The graph in Figure 5 is unambiguous, but it unfortunately is also more complex than the ambiguous graph in Figure 4. Even though this notation tends to produce complex graphs, it was preferred to producing ambiguous graphs. Current State-of-the-art Before developing SBML Viewer, the current state-of-the-art for SBML display was assessed. Numerous tools have been developed to represent networks in general, but there are rather few tools that actually display SBML networks. Since our goal is to provide tools that can be easily used to work on the biological networks models, an application that could produce a graphical representation directly from the SBML language was needed. After evaluation of the current state-of-the-art, the two most promising tools seemed to be BioSketchPad [5] and CellDesigner [6]. Both can be used to draw biological networks from SBML files. Unfortunately none of them was completely satisfying since they lacked one or both of the following important features: Automatic layout algorithms, which considerably reduce the work to layout complex networks. Support for self-reactions, which was critical in our model since many cells proliferate by themselves with a certain rate. Additionally, both were adding heavy graphing annotations to the SBML files to display them. These annotations contained information about the structure of the graph, which were redundant since it is already contained within the SBML code. This sometimes led to files containing almost as much annotation as SBML code. Due to these problems, we decided that the development of SBML Viewer was our best option to cover all the features we needed. Design Choices SBML Viewer is designed to be a light and easy-to-use tool. It is designed to give the user as few work as possible to layout a SBML model by using automatic layout tools in order to cut down the amount of work. Thus leading to this typical workflow from a raw SBML model to a graph and a simulation: 1. Load the SBML File 2. Use automatic layout algorithm(s) to get a first layout of the graph 3. Refine the automatic layout manually to get the desired representation of the biological network 4. Prepare the model for simulation by setting up its parameters and the species initial quantities. 5. Export the model to a Matlab file for simulation. Another important design constraint for SBML Viewer was to keep the SBML files light by adding as few displaying annotations as possible. In a SBML file, the structure of the biological network is totally and unambiguously described. The graph structure can therefore be read directly from the non-annotated SBML file and SBML Viewer only needs to add the position and the size of each species and reactions thus keeping the SBML files light and easy to read. As a part of our framework, SBML Viewer complies with its general guidelines: the code was written in Java (Java 1.4 compliant), and the SBML language is used for communication within the framework. Libraries I used 3 libraries to design SBML Viewer: libsbml [7] to import/export SBML files into java objects, JGraph [8] to create/edit the biological network and JGraphPad Community Edition [9] to automatically layout the network. I also used the Jigloo [10] GUI builder to construct the GUI. libsbml is a library written in ISO C and C++ by the SBML Research group and distributed under the GNU Lesser General Public License. It provides functions to: read SBML files and store them in memory as objects, getters/setters for these objects variables, export these objects to SBML files, syntactically and semantically check SBML files. LibSBML provides wrappers for several languages including java. I chose to use libsbml for the treatment of the SBML files and their structure in memory. I think it was a logical choice over generic XML libraries such as DOM since it provided tools to syntactically and semantically check SBML files and also provided the specific SBML structure.

5 JGraph is an open source java library originally written at the Swiss Institute of Technology in Zurich and distributed under the GNU Lesser General Public License. Among its large palette of components, it provides graphing tools for the structure and display of graphs, which were essential in the realization of SBML Viewer. JGraph was chosen because it is a widely used, reliable library that provides all the tools I needed to implement the biological networks in SBML Viewer. It was also linked to the JGraphPad Community Edition extension that would provide the automatic layout algorithm. Finally JGraph is free of charge. JGraphPad Community Edition is an open source extension of the JGraph library. I used its automatic layout functions for SBML Viewer. Features SBML Viewer had for main goals to give a graphical representation of biological networks and provide tools to prepare these networks for simulation. Therefore SBML Viewer provides functions to: Display biological networks using the graphical representation described in this paper from SMBL files. Manually layout a biological network without changing its connections. Automatically layout a biological network using several graph layout algorithms (detailed in the Automatic Layouts ). Export a biological network with annotations on its layout to a SBML file. Change names of species, reactions and parameters. Set the stoichiometry of species in reactions. Set initial concentrations or initial amount of species for a simulation. It was also designed to provide a GUI to the framework and therefore provides links to run the other components of the framework. It provides the following extra functions using the packages of M.Sede [2] and J.Eperon [3]: Transform a TSed [2] file into an SBML file and display it. Export a biological network to a LaTeX file. Export a biological network to MatLab for simulation. Automatic Layouts One of the main reasons I decided to build a new application to display biological networks was the lack of automatic layout functions in existing SBML graphing software. Biological networks typically involve large numbers of species and reactions and therefore tend to be very complex networks. When displaying them from a textual representation, there are no indications on how to display them; therefore when first importing a network from an SBML file, the graphing application needs to arrange the graph in a readable way. SBML Viewer provides four automatic layout algorithms from the JGraphPad Community Edition library [9] to address this problem. These algorithms try to arrange the graph in order for it to be readable; unfortunately complex graphs will still need some manual editing afterwards in order to arrange edges crossings, edge passing through vertices, vertices spacing and overlapping vertices. The idea behind providing four different algorithms is that the best result comes from a combination of multiple algorithms. I decided not to provide any macros to iteratively apply the algorithms; therefore it is up to the user to decide how many times to apply each algorithm and what combination to use. The following sections give an overview of the different algorithms as well as recommendation on their usage. To illustrate the output of the methods, the following sections will use the simple graph example shown in figure 6. Figure 6: Simple Graph Example

6 Simulated Annealing Layout Algorithm The simulated annealing layout algorithm is implemented from the work of R.Davidson and D.Harel, "Drawing Graphs Nicely Using Simulated Annealing" [11]. Its output minimizes the number of edges crossings but doesn t penalize vertices overlapping. Thus results in a good looking graph requiring few user works afterwards. Unfortunately the algorithm is very complex and requires lots of computing time, thus making it a bad candidate for large graphs. The algorithm is fully configurable through a dialog and details about its configuration can be found in the user manual and in [11]. The result of the simulated annealing layout algorithm on the simple graph example is shown in Figure 7. therefore the output usually is too compact. To correct this default, a good solution is to use it in conjunction with the GEM layout algorithm. This algorithm works fast and well, even for large graphs, but requires some user works after completion. The algorithm works iteratively and only requires the number of iterations as an input. The result of a 20 iterations spring embedded algorithm on the example simple graph is shown in Figure 8. Figure 8: Spring Embedded Layout on Simple Example Figure 7: Annealing Layout on Simple Example Spring Embedded Layout Algorithm The spring embedded layout algorithm available in SBML Viewer is the work of S.Luzar [12]. The spring embedded layout algorithm is very good at separating sub graphs from a complex graph and at separating strongly connected regions of a graph in general. Its solution comport minimum vertices overlapping but can result in extra edges crossings. Distances in between vertices of the strongly connected regions of the graph are usually small and Sugiyama Layout Algorithm The sugiyama layout algorithm is based on the work of K.Sugiyama and P.Eades: How to draw a directed graph [17]. The sugiyama layout algorithm is quick and good at separating sub graphs from a complex model. It is therefore highly recommended to use it when the model is composed of a number of small graphs. The output of this algorithm is quite well spaced. Unfortunately all the entities of a reaction are linearly aligned without caring for edges crossing vertices, which often leads to confusing representations. Nonetheless it is a very powerful algorithm that can eventually be applied to first space out the graph before applying other algorithms. The algorithm only has 4 parameters that can be configured through a configuration dialog. Details about its configuration can be found in the user manual and in [17]. The result of the sugiyama layout algorithm on the simple graph example is shown in Figure 9.

7 Conclusions Figure 9: Sugiyama Layout on Simple Example GEM Layout Algorithm The GEM layout algorithm is based on the work of A.Frick, A.Ludwig, H.Mehldau: "A Fast Adaptive Layout Algorithm for Undirected Graphs" [13]. Its output is a graph with few vertices overlapping and - although the algorithm doesn t explicitly minimize it reasonable edges crossings. Its downside is that it tends to output very spread out graphs; therefore combining this algorithm with the spring embedded is a great solution to automatically layout large and complex graphs. The algorithm is fully configurable through a dialog and details about its configuration can be found in the user manual and in [13]. The result of the annealing layout algorithm on the simple graph example is shown in Figure 10. Figure 10: GEM Layout on Simple Example Future Work The main area of extension for SBML Viewer would be to extend its editing capabilities. At the moment its functions are limited to laying out a biological network and configuring it for simulation. It would be valuable to extend this application so that graphs could be directly drawn and edited with it. With our current setup, biologists using our framework always have to use the text representation first before being able to see the network they are modelling. This method is relatively prone to errors since the text representation doesn t give a global view of the network. Another research topic for SBML Viewer would be to design and implement specific layout algorithms for biological networks. For example, M. Y. Becker and I. Rojas in A graph layout for drawing metabolic pathways [14] present an algorithm based on a combination of standard graph algorithms to take in account the structure of metabolic pathways. Such algorithms could lead to better automatic layout in SBML Viewer. Finally, SBML Viewer could be extended to support layered graph with sub graphs encapsulated. The SBML language provides a two layers structure with compartments containing the different reactions that could be added to SBML Viewer. Since our whole framework doesn t yet support this kind of structure, it would be a work that would have to be done on the whole framework. Skills Acquired Prior to the realization of the projects itself, a good understanding of the biological networks structure was necessary to understand the kind of relationships I would have to take in consideration, their complexity, and the modelling problem they would pose. Since the actual project of the LCA and the CHUV needs to model part of the immune system, it was a good idea to realize what actors and relations compose the immune system. Therefore I read the book by L. Sompayrac: How the Immune System Works [15], which proved to be a very interesting lecture and a good introduction to the project. During the design phase of the project, I had to explore and assess the programs and libraries

8 already available to realize the graphical display of a biological network. It was a very instructive process to analyze the current stateof-the-art in biological network displaying as well as in graphing libraries. I learned how to assess such programs and libraries using criteria like version, popularity, documentation, features, recognition and licensing. Since the whole framework uses SBML as a communication language, I had to study the structure of this language, its restrictions and applications. As SBML is a widely used communication language between bioinformatics applications, it will definitely be helpful to have experience with it for my future projects in this domain. During the coding part, I learned to use the libsbml and the JGraph libraries. The libsbml library was easy to use and provided mostly basic functions. It is nevertheless very well done and I would definitely use it again. JGraph is a hard library to work with since the only documentation freely available is the automatically generated Javadoc. Its general structure is quite complex and not very intuitive. Therefore it requires quite a bit of work to get into this library and be able to properly use it. Finally, attending all the meetings about the framework gave me a very good idea of how to simulate biological networks and the difficulties tied to this problem. References [1] The Systems Biology Markup Language Website (2006). Available on the World Wide Web at: [2] M. Sede (2006). Fast Chemical Reactions Modeling with TSed. Available on the World Wide Web at: [3] J. Eperon (2006). On modelling a biochemical process, from models to simulation. Available on the World Wide Web at: [4] A.Finney, M.Hucka (2003). Systems Biology Markup Language (SBML) Level 2: Structures and Facilities for Model Definitions. California Institute of Technology, Pasadena, USA [5] The Systems Biology Institute (2006). Cell Designer Website. Available on the World Wide Web at [6] Biocomputing Group at the University of Pennsylvania (2005). BioSketchPad Website. Available on the World Wide Web at /new_html/biosketch.php3 [7] The Systems Biology Markup Language Website (2006). libsbml Webpage. Available on the World Wide Web at: [8] JGraph Website (2006). Available on the World Wide Web at: [9] JGraph Diagram Component Project (2006). JGraphPad Library. Available on the World Wide Web at: [10] Cloud Garden (2006). Jigloo Website. Available on the Worl Wide Web at: [11] R. Davidson, D. Harel. Drawing graphs nicely using simulated annealing (1996). ACM Transactions on Graphing (TOG), Volume 15, Issue 4, pp ACM Press, New-York, USA [12] S. Luzar. SpringEmbedded LayoutAlgorithm java class. Available on the World Wide Web at: aph/layout/springembeddedlayoutalgo rithm.java.html [13] A.Frick, A.Ludwig, H.Mehldau (1994). "A Fast Adaptive Layout Algorithm for Undirected Graphs". Proceedings of the DIMACS International Workshop on Graph Drawing, pp , Springer- Verlag, London, UK [14] M. Y. Becker and I. Rojas (2001). A graph layout for drawing metabolic pathways. Bioinformatics, Volume 17, pp [15] L. Sompayrac (2003). How the Immune System Works, 2 nd Edition. Blackwell Science, Oxford, UK [16] Compendium of Biochemical Nomenclature and Related Documents (1992), pp Portland Press, London, UK. [17] K.Sugiyama, P.Eades (1991). How to draw a directed graph. Journal of Information Processing, volume 13, issue 4, pp Processing Society of Japan, Tokyo, Japan.