Harmony Posters

Poster 1

 * Benjamin Gross, Ethan Cerami, Emek Demir, Igor Rodchenkov, Nadia Anwar, Nikki Schultz and Chris Sanderand Gary Bader
 * Aggregation and Integration of Pathway Databases in PathwayCommons
 * Pathway Commons is a collection of publicly available pathway data from multiple organisms. Pathway Commons provides a web-based interface that enables biologists to browse and search a comprehensive collection of pathways from multiple sources represented in a common language, a download site that provides integrated bulk sets of pathway information in standard or convenient formats, and a web service that software developers can use to conveniently query and access all data. Database providers can share their pathway data via a common repository. Pathways include biochemical reactions, complex assembly, transport and catalysis events, and physical interactions involving proteins, DNA, RNA, small molecules and complexes. Pathway Commons aims to collect all available pathway data available in standard formats and currently integrates data from nine public databases and contains over 1400 pathways and 400,000 interactions.

Poster 2
Authors: M.P. van Iersel (1, 2) S.E. Boyd (3)  F. Bergmann (4)  S. Moodie (5)  F. Schreiber (6, 7)  T. Czauderna (6)  E. Demir (8)  N. Le Novère (9)  A. Sorokin (10)  H. Mi (11)  A. Luna (12, 13)  U. Dogrusoz (14)  Y. Matsuoka (15)  A. Funahashi (16)  H. Kitano (15, 17, 18)  M.I. Aladjem (12)  M.L. Blinov (19)  A.C. Villeger (20, 21)
 * LibSBGN Community and Martijn van Iersel
 * '''LibSBGN: electronic exchange of SBGN maps
 * LibSBGN: Electronic Processing of SBGN maps

Affiliations: 1)Department of Bioinformatics BiGCaT, Maastricht University, Maastricht, The Netherlands. 2)Netherlands Consortium for Systems Biology (NCSB), The Netherlands. 3)AgriBio, La Trobe University, Melbourne, Australia. 4)Department of Bioengineering, University of Washington, Seattle, Washington, USA. 5)Centre for Systems Biology at Edinburgh, University of Edinburgh, Edinburgh, UK. 6)Leibniz Institute of Plant Genetics and Crop Plant Research, Gatersleben, Germany. 7)Institute of Computer Science, Martin Luther University Halle-Wittenberg, Germany 8)Memorial Sloan Kettering Cancer Center - Computational Biology Center, New York, NY, USA. 9)EMBL European Bioinformatics Institute, Hinxton, UK. 10)School of Informatics, University of Edinburgh, Edinburgh, UK. 11)SRI International, Menlo Park, California, USA. 12)National Cancer Institute, Bethesda, Maryland, USA. 13)Department of Bioinformatics, Boston University, Boston, MA, USA 14)Bilkent Center for Bioinformatics, Bilkent University, Ankara, Turkey. 15)The Systems Biology Institute, Tokyo, Japan. 16)Department of Biosciences and Informatics, Keio University, Yokohama, Japan. 17)Okinawa Institute of Science and Technology, Okinawa, Japan.  18)Sony Computer Science Laboratories, Tokyo, Japan. 19)Department of Computational Biology, University of Pittsburgh School of Medicine, USA. 20)School of Computer Science, University of Manchester, Manchester, UK. 21)Manchester Interdisciplinary Biocentre, Manchester, UK.

Introduction: Graphical representations of participants and their relationships are essential for exchanging knowledge about complex biological processes. To convey this information clearly and unambiguously, it is necessary to assign standard meanings to symbols and their connectivity. For this purpose, the System Biology Graphical Notation (SBGN) has been developed. As SBGN is becoming more widely adopted, and used in various software tools, there is an increasing need for a standard file format able to capture the SBGN maps. Exchange using graphics-only file formats (such as SVG) is insufficient, because the biological meaning of elements is lost. There is a need for a toolset that enables diagram exchange while preserving biological meaning and relations. Results: To meet this need, we are developing an Extensible Markup Language (XML) schema definition. In addition we are developing a software library called LibSBGN. Besides reading and writing files, this library will also be used to validate SBGN maps against the specifications, and convert to and from related systems biology standards, such as SBML and BioPAX. LibSBGN is still under development, but is already being adopted by several tools (See the LibSBGN project page for an up-to-date list of client software). The early adoption of LibSBGN by those tools helps to ensure that LibSBGN is independent of a specific software application, and does not contain artifacts for specific tools. LibSBGN is currently implemented in Java, a parallel C++ version is planned for the future. A test-suite of dozens of LibSBGN documents, covering every possible feature of SBGN maps, was created. This test-suite can be used by developers to check for compliance with the standard, and compare rendering capabilities with other tools. LibSBGN is a community effort, involving people from institutes all around the world, representing a wide selection of pathway tools. The community is organized around a sourceforge project site (http://libsbgn.sourceforge.net), a mailing list and monthly online meetings. A first release of LibSBGN, covering only the Process Description (PD) language, has been released in January 2011. Support for all three languages of SBGN is planned for a later release.

Poster 3

 * Robin Haw, David Croft, Guanming Wu, Marija Orlic-Milacic, Ewan Birney, Henning Hermjakob, Peter D'Eustachio and Lincoln Stein
 * Reactome: A Knowledgebase of Biological Pathways

Poster 4

 * Cooling M. T.
 * CellML Metadata Framework 2.0	
 * In the last ten years model encoding efforts such as CellML and SBML have greatly facilitated model availability. As the complexity of models increases, usefulness of these models can be variable. The addition of semantic information is key to moving model encodings from esoteric to informative resources. Here we describe a modular metadata framework consisting of satellite specifications for several immediately-useful domains of interest. We also look ahead to several challenges that we will need to address in version 3.0.

Poster 5

 * Cooling M.T., Nickerson D. P., Miller A. K., Terkildsen J., Wimalaratne S. M., Nielsen P. M. F.,
 * Best Practices for Modular Model Encoding with CellML 1.1
 * CellML 1.1 is a model-exchange protocol designed to aid model construction, simulation, analysis and communication. With intrinsic support for model modularity and domain-neutral syntax, CellML is facilitating successful research in both Systems and Synthetic Biology. The language allows great flexibility in defining sub-models and the connections between them, encouraging innovation. As repositories of reusable mathematical models become more critical to research, guidelines are needed to ensure that modular models are developed so that they can be easily combined to form expressive models. These guidelines will enable the faster and more accurate development of new models of biological systems of interest.

Poster 6

 * David Nickerson, Andrew Miller, Lukas Endler, Randall Britten, Poul Nielsen
 * CellML 1.2 and beyond	
 * In this poster we will present an overview of current progress toward the next version of CellML. One of the main changes from CellML 1.1 is that future versions of CellML will consist of a broad specification of "fundamental CellML concepts" and secondary specifications that narrow the scope of the fundamental concepts for particular types of models being represented in CellML. For example, a secondary specification allowing for the description of index-1 DAE models not involving simultaneous equations and only using a restricted subset of MathML 2.0 would encompass most models models currently encoded in CellML and able to be simulated using existing tools. Secondary specifications narrow the scope such that software support for the complete specification is possible in terms of being able to run numerical simulations based on the model encoding, while allowing other types of tools (i.e., editing and/or presentation environments) to be generic. Under this paradigm, we are proposing that CellML 1.2 will be a collection of the fundamental concepts specification and associated secondary specifications that narrow the scope to that which is supported by the CellML Integration Service in the CellML API implementation. Features being considered for inclusion in CellML 1.2 include variable typing and changes to grouping and connections. In addition, we are considering what is required in the fundamental concepts specification so secondary specifications can allow support for events, reset rules, and delays.

Poster 7

 * David Nickerson, Tommy Yu, Randall Britten, Poul Nielsen
 * PMR2: The Software Framework Behind the Physiome Model Repository
 * PMR (physiome model repository) originated as a static website housing the example CellML models developed in concert with the CellML XML model encoding specification. The software consisted of a series of utilities which turned a collection of CellML documents into static HTML pages. As the requirements of the CellML model repository grew beyond a simple archive of examples, this software framework was transitioned to an object database (Zope) and associated web portal (Plone). This development provided improvement in the functionality available to the community in regard to retrieving CellML models and the information contained therein. However, the addition of new models and editing of existing models were features only available to repository managers. Also, the advent of CellML 1.1 introduced features that PMR was unable to utilise. Support of these features was inhibited by the implementation of PMR, so the decision was made to re-write the software. This new software is known as PMR2.   While still being based in Zope and Plone, PMR2 has substantially changed the way models are stored in the repository. The basic unit of the repository is a workspace. Each workspace is an independent version controlled repository of data. Workspaces have integrated user access controls, allowing the owner of each workspace to control who can access (read, write, both) the data. Repository users are able to browse any workspace they are entitled to access via the web portal (including historical revisions). Workspace owners are able to publish specific revisions of their workspaces to stable web addresses where user friendly documentation can be presented to the user. This publication process exposes a static revision of workspace in the model repository, which is known as an exposure. With no restriction on the types of data contained in a workspace, PMR2 is now able to include a greater range of model description formats. The only restriction is that in order to generate the exposure pages PMR2 needs to know about the data to be presented. As it is primarily designed for use with the Physiome Project, support for physiome model encoding formats has been the priority for development. As such, CellML models are well supported and as of version 0.3 PMR2 will support the draft FieldML standard. This advance will allow users to interact with 3-D anatomical models within the model repository web front end using the zinc extension for Firefox (cmiss.org/cmgui/zinc).

Poster 8

 * Ashok Reddy Dinasarapu, Kenan Azam, Brian Saunders, Shankar Subramaniam
 * Signaling Gateway Molecule Pages
 * The Signaling Gateway Molecule Pages (SGMP) database provides authored data on mammalian proteins which exist in different functional states participating in signal transduction pathways. State transitions are associated with one or more biological processes. In a characterized biological context a state can function as one of several entities or their combinations, including channel, enzyme, receptor, transcription factor and transporter. We have also exported SGMP data to the Biological Pathway Exchange (BioPAX) and Systems Biology Markup Language (SBML).

Poster 9

 * Andreas Dräger, Alexander Dürr, Clemens Wrzodek, Roland Keller, Andreas Zell
 * From KEGG to dynamic pathway models
 * Modeling of biochemical processes has gained lots of attention. In several projects, researchers laboriously gather reaction pathways and kinetic information with the aim to construct large-scale biochemical network models. When dealing with these models dedicated software tools are indispensable to facilitate the complicated and highly errorprone model building process. Here we present a collection of specifically developed SBML-based tools for this purpose.

Poster 10

 * Martina Kutmon, Martijn P. van Iersel, Chris T. Evelo
 * Remodeling of PathVisio's Plug-in System using OSGi
 * The interpretation of biological, experimental data consists of complex workflows involving multiple databases and tools. Between steps it is often necessary to switch from one tool to another. These switches require adjustments of the data to meet the necessary input constraints of subsequent tools. To increase user-friendliness and reduce errors it is desirable to use a minimum number of different software packages. The demand for increased functionality in a single piece of software must be balanced by the need for modularity to keep the software maintainable. In complex software, the conflicting demands of features and maintainability could be solved with plug-in systems. PathVisio (http://www.pathvisio.org) is a tool to visualize and edit biological pathways. Currently PathVisio is used to graphically represent biological datasets and to help with the interpretation. It is also used as the pathway editing tool within the open, collaborative pathway-curation platform WikiPathways. The current plug-in system of PathVisio is simple and easy to use. However, the increasing complexity of plug-ins demands more functionality. Dependencies and communication between plug-ins are key-features not supported by the current system. Inspired by the trend towards established modularity frameworks of similar projects, like Cytoscape or Protege, the developers decided to use the modularity framework OSGi to solve the current issues and problems. To ease the development of software tools the application is separated into smaller logical parts, which are implemented individually. Together, a set of modules can form a larger application. OSGi allows to build an infrastructure into an application to add and use different modules. It provides mechanisms to allow the individual modules to rely on and interact with each other, opening the possibility to put together different modules to solve the problem at hand. Some of these modules are going to be specific for one application but a lot of these modules can actually be reused by other tools. We are talking about general features like the import or export of different file formats, an layouting algorithm that could be used by several visualization tools or the lookup in an external online database. Why does every tool has to implement its own parser or algorithm? Modularity can help to share functionality. There is no need to start from scratch and implement everything anew, thus developers can focus on new and important features. With OSGi we want to facilitate the plug-in development but also the usage and installation of new plug-ins. A simple plug-in manager will help users to find, install and use existing plug-ins. Every user can decide which plug-ins he wants to use and when. The integration of new functionality to the PathVisio core application increases the usability of the software tool and furthermore the speed of the analysis process itself. To demonstrate the advantages of OSGi for plug-in systems, we plan to add GeneOntology analysis methods through plug-ins into PathVisio. For the development of these plug-ins we will reuse existing open source tools, e.g. GO-Elite. This shows how stand-alone parts of an analysis process can be combined within one framework using plug-ins.

Poster 11

 * Michael L. Blinov, James C. Schaff, Ion I. Moraru, Michael L. Blinov
 * Combining rule-based and reaction networks modeling approaches
 * We have witnessed an explosive growth in research involving mathematical models and computer simulations of intracellular molecular interactions, ranging from metabolic pathways to signaling and gene regulatory networks. Many software tools have been developed to aid in the study of such biological systems, some of which have a wealth of features for model building and visualization, and powerful capabilities for simulation and data analysis. Novel high resolution and/or high throughput experimental techniques have led to an abundance of qualitative and quantitative data related to the spatiotemporal distribution of molecules and complexes, their interactions kinetics, and functional modifications. Based on this information, computational biology researchers are attempting to build larger and more detailed models. However, this has proved to be a major challenge. Traditionally, modeling tools require the explicit specification of all molecular species and interactions in a model, which can quickly become a major limitation in the case of complex networks, as discussed below. Recently, a new breed of software tools has been created to address the problems faced when building models marked by combinatorial complexity. These have a different approach for model specification, using rules and patterns. Here we describe how to combine the capabilities of conventional simulation software with the unique features and flexibility of a rule-based approach in a single software platform for building models of molecular interaction networks.

Poster 12

 * Tobias Czauderna, Christian Klukas, Falk Schreiber
 * Editing, Validating, and Translating of SBGN Maps with SBGN-ED
 * The recently proposed Systems Biology Graphical Notation (SBGN) provides a standard for the visual representation of biochemical and cellular processes. Three different views (Process Description, Entity Relationship, and Activity Flow) cover several aspects of the represented processes in different levels of detail. To support SBGN, methods and tools for editing, validating, and translating of SBGN maps are necessary. We present methods for these tasks and SBGN-ED, a tool which allows to create all three types of SBGN maps from scratch, to validate these maps for syntactical and semantical correctness, to translate maps from the KEGG and MetaCrop databases into SBGN, and to export SBGN maps into several file and image formats. For more information see also Czauderna, Klukas, Schreiber: Editing, Validating, and Translating of SBGN Maps. Bioinformatics, 26(18):2340-2341 (2010) and http://www.sbgn-ed.org.