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Standard graphical representations have played a crucial role in science and engineering throughout the last century. Without electrical symbolism, it is very likely that our industrial society would not have evolved at the same pace. Similarly, specialised notations such as the Feynmann notation or the process flow diagrams did a lot for the adoption of concepts in their own fields. With the advent of Systems Biology, and more recently of Synthetic Biology, the need for precise and unambiguous descriptions of biochemical interactions has become more pressing. While some ideas have been advanced over the last decade, with a few detailed proposals, no actual community standard has emerged. The Systems Biology Graphical Notation (SBGN) is a graphical representation crafted over several years by a community of biochemists, modellers and computer scientists. Three orthogonal and complementary languages have been created, the Process Diagrams, the Entity Relationship Diagrams and the Activity Flow Diagrams. Using these three idioms a scientist can represent any network of biochemical interactions, which can then be interpreted in an unambiguous way. The set of symbols used is limited, and the grammar quite simple, to allow its usage in textbooks and its teaching directly in high schools. The first level of the SBGN Process Diagram has been publicly released. Software support for SBGN Process Diagram was developed concurrently with its specification in order to speed-up public adoption. Shared by the communities of biochemists, genomicians, theoreticians and computational biologists, SBGN languages will foster efficient storage, exchange and reuse of information on signalling pathways, metabolic networks and gene regulatory maps.

With the rise of Systems Biology as a new paradigm for understanding biological processes, the development of quantitative models is no longer restricted to a small circle of theoreticians. The dramatic increase in the number of these models precipitates the need to exchange and reuse both existing and newly created models. The Systems Biology Markup Language (SBML) is a free, open, XML-based format for representing quantitative models of biological interest that advocates the consistent specification of such models and thus facilitates both software development and model exchange. Principally oriented towards describing systems of biochemical reactions, such as cell signalling pathways, metabolic networks and gene regulation etc., SBML can also be used to encode any kinetic model. SBML offers mechanisms to describe biological components by means of compartments and reacting species, as well as their dynamic behaviour, using reactions, events and arbitrary mathematical rules. SBML also offers all the housekeeping structures needed to ensure an unambiguous understanding of quantitative descriptions. This specification presents the structures of the language and the rules used to build a valid model. SBML XML Schema and other related documents and software are also available from the SBML project web site, "http://sbml.org/":http://sbml.org/.

The Systems Biology Markup Language (SBML) is a machine-readable model representation language for software tools in computational systems biology. By supporting SBML as an input/output format, different tools can all operate on an identical representation of a model, removing opportunities for translation errors and assuring a common starting point for analyses and simulations. SBML is by no means a perfect format, but it has achieved widespread acceptance as a de facto standard. It is supported worldwide by over 100 software systems (both open-source and commercial). The broad acceptance of a common, open format for exchanging models between software tools is a crucial step towards wider use of quantitative modeling in biology, because it allows researchers to build upon each other's work with greater ease and accuracy.SBML can encode models consisting of biochemical entities (species) linked by reactions to form networks. An important principle is that models are decomposed into explicitly-labeled constituent elements, the set of which resembles a verbose rendition of chemical reaction equations. The representation deliberately does not cast the model directly into a set of differential equations or other specific interpretation of the model. The formalisms in SBML allows a wide range of biological phenomena to be modeled, including metabolism, cell signaling, gene regulation, and more. Significant flexibility and power comes from the ability to define arbitrary formulae for the rates of change of variables as well as the ability to express other constraints mathematically.This tutorial covered the latest edition of SBML, which is Level 2 Version 2, finalized in September 2006. Topics covered include the basic common principles in SBML as well the changes introduced in Level 2 Version 2. We also discussed software tools for programmers, in particular libSBML.

MathSBML is an open-source, freely downloadable Mathematica package that facilitates working with Systems Biology Markup Language (SBML) models. SBML is a tool-neutral, computer-readable format for representing models of biochemical reaction networks, and it is applicable to metabolic networks, cell signaling pathways, genomic regulatory networks, and other modeling problems in systems biology that is widely supported by the systems biology community. SBML is based on XML, which is a standard medium for representing and transporting data that is widely supported on the Internet, as well as in computational biology and bioinformatics. Because SBML is tool-independent, it enables model transportability, reuse, publication, and survival. In addition to Math- SBML, a number of other tools that support SBML model examination and manipulation are provided on the http://sbml.org Web site, including libSBML, which is a C/C++ library for reading SBML models; an SBML Toolbox for MATLAB; file conversion programs; an SBML model validator and visualizer; and SBML specifications and schemas. MathSBML enables SBML file import to and export from Mathematica, as well as providing an API for model manipulation and simulation.

Biologists are increasingly recognising that computational modelling is crucial for making sense of the vast quantities of complex experimental data that are now being collected. The systems biology field needs agreed-upon information standards if models are to be shared, evaluated and developed cooperatively. Over the last four years, our team has been developing the Systems Biology Markup Language (SBML) in collaboration with an international community of modellers and software developers. SBML has become a de facto standard format for representing formal, quantitative and qualitative models at the level of biochemical reactions and regulatory networks. In this article, we summarise the current and upcoming versions of SBML and our efforts at developing software infrastructure for supporting and broadening its use. We also provide a brief overview of the many SBML-compatible software tools available today.

The objective of the research is to develop mathematical and software infrastructure in support of post-genomics research in systems biology. One objective articulated in this effort centers on a deeper understanding of the organizational principles of biological networks. A distinguishing theme of this work is its focus on scalable methods of robustness and model validation and invalidation with data, as opposed to relying purely on simulation. The Systems Biology Markup Language (SBML) project is a machine-readable exchange language for computational models of biochemical networks. LibSBML, an embedded software library for SBML, was developed, providing an application programming interface for working with SBML. The LibSBML library provides an interface for working with SBML in a number of programming languages: C, C++, Java, Perl, MATLAB, Lisp, and Python. It is free, open-source, and portable to Linux, Windows, MacOS and Solaris. The effort led to (1) continued development of LibSBML, (increased support of SBML features and added functionality); and (2) supported SBML use and evolution (direct support for DARPA Bio-SPICE).

Formalized rules for protein-protein interactions have recently been introduced to represent the binding and enzymatic activities of proteins in cellular signaling. Rules encode an understanding of how a system works in terms of the biomolecules in the system and their possible states and interactions. A set of rules can be as easy to read as a diagrammatic interaction map, but unlike most such maps, rules have precise interpretations. Rules can be processed to automatically generate a mathematical or computational model for a system, which enables explanatory and predictive insights into the system’s behavior. Rules are independent units of a model specification that facilitate model revision. Instead of changing a large number of equations or lines of code, as may be required in the case of a conventional mathematical model, a protein interaction can be introduced or modified simply by adding or changing a single rule that represents the interaction of interest. Rules can be defined and visualized by using graphs, so no specialized training in mathematics or computer science is necessary to create models or to take advantage of the representational precision of rules. Rules can be encoded in a machine-readable format to enable electronic storage and exchange of models, as well as basic knowledge about protein-protein interactions. Here, we review the motivation for rule-based modeling; applications of the approach; and issues that arise in model specification, simulation, and testing. We also discuss rule visualization and exchange and the software available for rule-based modeling.

Summary: CellML and SBML are XML-based languages for storage and exchange of molecular biological and physiological reaction models. They use very similar subsets of MathML to specify the mathematical aspects of the models. CellML2SBML is implemented as a suite of XSLT stylesheets that, when applied consecutively, convert models expressed in CellML into SBML without significant loss of information. The converter is based on the most recent stable versions of the languages (CellML version 1.1; SBML Level 2 Version 1), and the XSLT used in the stylesheets adheres to the XSLT version 1.0 specification. Of all 306 models in the CellML repository in April 2005, CellML2SBML converted 91% automatically into SBML. Minor manual changes to the unit definitions in the originals raised the percentage of successful conversions to 96%. Availability: Contact: m.j.1.schilstra@herts.ac.uk Supplementary information: Instructions for use and further documentation available on

Until recently, the majority of computational models in biology were implemented in custom programs and published as statements of the underlying mathematics. However, to be useful as formal embodiments of our understanding of biological systems, computational models must be put into a consistent form that can be communicated more directly between the software tools used to work with them. In this chapter, we describe the Systems Biology Markup Language (SBML), a format for representing models in a way that can be used by different software systems to communicate and exchange those models. By supporting SBML as an input and output format, different software tools can all operate on an identical representation of a model, removing opportunities for errors in translation and assuring a common starting point for analyses and simulations. We also take this opportunity to discuss some of the resources available for working with SBML as well as ongoing efforts in SBML’s continuing evolution.

BioModels Database (http://www.ebi.ac.uk/biomodels/), part of the international initiative BioModels.net, provides access to published, peer-reviewed, quantitative models of biochemical and cellular systems. Each model is carefully curated to verify that it corresponds to the reference publication and gives the proper numerical results. Curators also annotate the components of the models with terms from controlled vocabularies and links to other relevant data resources. This allows the users to search accurately for the models they need. The models can currently be retrieved in the SBML format, and import/export facilities are being developed to extend the spectrum of formats supported by the resource.

Most of the published quantitative models in biology are lost for the community because they are either not made available or they are insufficiently characterized to allow them to be reused. The lack of a standard description format, lack of stringent reviewing and authors' carelessness are the main causes for incomplete model descriptions. With today's increased interest in detailed biochemical models, it is necessary to define a minimum quality standard for the encoding of those models. We propose a set of rules for curating quantitative models of biological systems. These rules define procedures for encoding and annotating models represented in machine-readable form. We believe their application will enable users to (i) have confidence that curated models are an accurate reflection of their associated reference descriptions, (ii) search collections of curated models with precision, (iii) quickly identify the biological phenomena that a given curated model or model constituent represents and (iv) facilitate model reuse and composition into large subcellular models.

The recent work of Kitano et al on a comprehensive EGFR Pathway Map (Mol Systems Biol, this issue) represents a tremendous amount of intellectual effort. The scale of the model is breathtaking. No doubt some readers will assail the effort on the grounds that models of this size and complexity are difficult to verify, but while this may be true for today’s methods, it is an unhelpful criticism. The inescapable reality in systems biology is that models (that is to say, hypotheses cast in a computational form) will continue to grow in size, complexity, and scope. Rather than grouse, we should be thinking about how to developways of analyzing and verifying models of this scale. We also need to improve our methods of sharing and understanding each other’s work in order to facilitate the iterative processes of review and refinement that are fundamental to modeling.

The SBML (systems biology markup language) is a standard exchange format for computational models of biochemical networks. We continue developing SBML collaboratively with the modelling community to meet their evolving needs. The recently introduced SBML Level 2 includes several enhancements to the original Level 1, and features under development for SBML Level 3 include model composition, multistate chemical species and diagrams.

Researchers in quantitative systems biology make use of a large number of different software packages for modelling, analysis, visualization, and general data manipulation. In this paper, we describe the Systems Biology Workbench (SBW), a software framework that allows heterogeneous application components--written in diverse programming languages and running on different platforms--to communicate and use each others' capabilities via a fast binary encoded-message system. Our goal was to create a simple, high performance, opensource software infrastructure which is easy to implement and understand. SBW enables applications (potentially running on separate, distributed computers) to communicate via a simple network protocol. The interfaces to the system are encapsulated in client-side libraries that we provide for different programming languages. We describe in this paper the SBW architecture, a selection of current modules, including Jarnac, JDesigner, and SBWMeta-tool, and the close integration of SBW into BioSPICE, which enables both frameworks to share tools and compliment and strengthen each others capabilities.

A realistic neuronal model represents a modeler's understanding of the structure and function of a part of the nervous system. The increasing number of such models represents a significant accumulation of knowledge about the structural and functional organization of nervous systems. However, locating appropriate models and interpreting them becomes increasingly more difficult as the number of online model and experimental databases grows. The central motivation for the Modeler's Workspace project is to address these problems. The Modeler's Workspace is a collection of software tools being created to enable users to interact with databases of models and data. It will provide facilities for: searching multiple remote databases for model components based on various criteria; visualizing the characteristics of the components retrieved; creating new components, either from scratch or derived from existing models; combining components into new models; linking models to experimental data as well as online publications; and interacting with simulation packages such as GENESIS to simulate the new constructs. It is being written in Java for portability and extensibility. It is modular in design and uses pluggable components. To increase the probability that the Modeler's Workspace will be compatible with future databases and tools, we arc using the XML, the eXtensible Markup Language, as the interchange format for communicating with databases.

Motivation: Molecular biotechnology now makes it possible to build elaborate systems models, but the systems biology community needs information standards if models are to be shared, evaluated and developed cooperatively. Results: We summarize the Systems Biology Markup Language (SBML) Level 1, a free, open, XML-based format for representing biochemical reaction networks. SBML is a software-independent language for describing models common to research in many areas of computational biology, including cell signaling pathways, metabolic pathways, gene regulation, and others. Availability: The specification of SBML Level 1 is freely available from http://www.sbml.org/ Contact: sysbio-team@caltech.edu * To whom correspondence should be addressed.

Amit's efforts to provide stronger theoretical and empirical support for Hebb's cell-assembly concept is admirable, but we have serious reservations about the perspective presented in the target article. For Hebb, the cell assembly was a building block; by contrast, the framework proposed here eschews the need to fit the assembly into a broader picture of its function.

Nat. Biotechnol. 27 735–741 (2009); published online 7 August 2009; corrected after print 11 August 2009 In the version of this article initially published, the wrong versions of Figures 1, 2 and 3 were used. The error has been corrected in the HTML and PDF versions of the article.

The Computational Modeling in Biology Network (COMBINE, http://co.mbine.org/), an initiative whose goal is to coordinate the development of the various community standards and formats in computational systems biology and related fields. This report summarises the activities pursued at the first annual COMBINE meeting held in Edinburgh on October 6-9 2010 and the first HARMONY hackathons, held in New-York on April 18-22 2011. The first of those meetings hosted 81 attendees, and discussions covered not only the standards part of COMBINE such as BioPAX, SBGN and SBML, but emerging efforts and interoperability between the different formats. The second meeting, oriented towards developers, welcomed 59 participants and witnessed many technical discussions and development enhancing software support of the standards, and conversion between them. Both meetings were resounding successes and showed that the field is now mature enough to develop representation formats and related standards in a coordinated manner.

Circuit diagrams and Unified Modeling Language diagrams are just two examples of standard visual languages that help accelerate work by promoting regularity, removing ambiguity and enabling software tool support for communication of complex information. Ironically, despite having one of the highest ratios of graphical to textual information, biology still lacks standard graphical notations. The recent deluge of biological knowledge makes addressing this deficit a pressing concern. Toward this goal, we present the Systems Biology Graphical Notation (SBGN), a visual language developed by a community of biochemists, modelers and computer scientists. SBGN consists of three complementary languages: process diagram, entity relationship diagram and activity flow diagram. Together they enable scientists to represent networks of biochemical interactions in a standard, unambiguous way. We believe that SBGN will foster efficient and accurate representation, visualization, storage, exchange and reuse of information on all kinds of biological knowledge, from gene regulation, to metabolism, to cellular signaling. © 2009 Nature America, Inc.

Researchers in computational biology today make use of a large number of different software packages for modeling, analysis, and data manipulation and visualization. In this paper, we describe the ERATO Systems Biology Workbench (SBW), a software framework that allows these heterogeneous application components--written in diverse programming languages and running on different platforms--to communicate and use each others' data and algorithmic capabilities. Our goal is to create a simple, open-source software infrastructure which is effective, easy to implement and easy to understand. SBW uses a broker-based architecture and enables applications (potentially running on separate, distributed computers) to communicate via a simple network protocol. The interfaces to the system are encapsulated in client-side libraries that we provide for different programming languages. We describe the SBW architecture and the current set of modules, as well as alternative implementation technologies.

In common with many fields, including astronomy, a vast number of software tools for computational modeling and simulation are available today in systems biology. This wealth of resources is a boon to researchers, but it also presents interoperability problems. Despite working with different software tools, researchers want to disseminate their work widely as well as reuse and extend the models of other researchers. This situation led in the year 2000 to an effort to create a tool-independent, machine-readable file format for representing models: SBML, the Systems Biology Markup Language. SBML has since become the de facto standard for its purpose. Its success and general approach has inspired and influenced other community-oriented standardization efforts in systems biology. Open standards are essential for the progress of science in all fields, but it is often difficult for academic researchers to organize successful community-based standards. I draw on personal experiences from the development of SBML and summarize some of the lessons learned, in the hope that this may be useful to other groups seeking to develop open standards in a community-oriented fashion.