Systems Biology Graphical Notation: Process Description language Level 1

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

Systems Biology Graphical Notation: Process Description language Level 1

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

Systems Biology Graphical Notation: Activity Flow language Level 1

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, specialized 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 Descriptions, the Entity Relationships and the Activity Flows. 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 ranging from textbooks and teaching in high schools to peer reviewed articles in scientific journals. The first level of the SBGN Activity Flow language has been publicly released. Shared by the communities of biochemists, genomic scientists, theoreticians and computational biologists, SBGN languages will foster efficient storage, exchange and reuse of information on signaling pathways, metabolic networks and gene regulatory maps

Fast multi-core based multimodal registration of 2D cross-sections and 3D datasets

<p>Abstract</p> <p>Background</p> <p>Solving bioinformatics tasks often requires extensive computational power. Recent trends in processor architecture combine multiple cores into a single chip to improve overall performance. The Cell Broadband Engine (CBE), a heterogeneous multi-core processor, provides power-efficient and cost-effective high-performance computing. One application area is image analysis and visualisation, in particular registration of 2D cross-sections into 3D image datasets. Such techniques can be used to put different image modalities into spatial correspondence, for example, 2D images of histological cuts into morphological 3D frameworks.</p> <p>Results</p> <p>We evaluate the CBE-driven PlayStation 3 as a high performance, cost-effective computing platform by adapting a multimodal alignment procedure to several characteristic hardware properties. The optimisations are based on partitioning, vectorisation, branch reducing and loop unrolling techniques with special attention to 32-bit multiplies and limited local storage on the computing units. We show how a typical image analysis and visualisation problem, the multimodal registration of 2D cross-sections and 3D datasets, benefits from the multi-core based implementation of the alignment algorithm. We discuss several CBE-based optimisation methods and compare our results to standard solutions. More information and the source code are available from <url>http://cbe.ipk-gatersleben.de</url>.</p> <p>Conclusions</p> <p>The results demonstrate that the CBE processor in a PlayStation 3 accelerates computational intensive multimodal registration, which is of great importance in biological/medical image processing. The PlayStation 3 as a low cost CBE-based platform offers an efficient option to conventional hardware to solve computational problems in image processing and bioinformatics.</p

Visualisierung biochemischer Reaktionsnetze

In dieser Arbeit werden Anforderungen an die Darstellung biochemischer Reaktionsnetze untersucht und die Netze unter dem Gesichtspunkt der Visualisierung modelliert. Anschliessend wird ein Algorithmus zum Zeichnen biochemischer Reaktionsnetze entwickelt und analysiert.In this dissertation we investigate the requirements for the visualisation of biochemical reaction networks. We compose a model for these networks that lends itself to visualisation and develop and analyse an algorithm to create drawings of the networks

Systems Biology Graphical Notation: Entity Relationship language Level 1

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 Descriptions, the Entity Relationships and the Activity Flows. 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 Entity Relationship language has been publicly released. 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

Novel developments in SBGN-ED and applications

Systems Biology Graphical Notation (SBGN, http://sbgn.org) [1] is an emerging standard for graphical representations of biochemical and cellular processes studied in systems biology. Three different views (Process Description, Entity Relationship, and Activity Flow) cover several aspects of the represented processes in different levels of detail. SBGN helps to communicate biological knowledge more efficient and accurate between different research communities in the life sciences. However, to support SBGN, methods and tools for editing, validating, and translating of SBGN maps are necessary.&#xd;&#xa;We present methods for these tasks and novel developments in SBGN-ED (www.sbgn-ed.org) [2], 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 database into SBGN, and to export SBGN maps into several file and image formats. SBGN-ED is based on VANTED (Visualization and Analysis of NeTworks containing Experimental Data, http://www.vanted.org) [3].&#xd;&#xa;As applications of SBGN and SBGN-ED we present furthermore MetaCrop (http://metacrop.ipk-gatersleben.de) [4], a database that summarizes diverse information about metabolic pathways in crop plants, and RIMAS (Regulatory Interaction Maps of Arabidopsis Seed Development, http://rimas.ipk-gatersleben.de) [5], an information portal that provides a comprehensive overview of regulatory pathways and genetic interactions during Arabidopsis embryo and seed development. &#xd;&#xa;&#xd;&#xa;[1] Le Nov&#xe8;re, N. et al. (2009) The Systems Biology Graphical Notation. Nature Biotechnology, 27, 735-741.&#xd;&#xa;[2] Czauderna, T., Klukas, C., Schreiber, F. (2010) Editing, validating, and translating of SBGN maps. Bioinformatics, 26 (18), 2340-2341.&#xd;&#xa;[3] Junker, B.H., Klukas, C., Schreiber, F. (2006) VANTED: A system for advanced data analysis and visualization in the context of biological networks. BMC Bioinformatics, 7, 109+.&#xd;&#xa;[4] Grafahrend-Belau, E., Weise, S., Kosch&#xfc;tzki, D., Scholz, U., Junker, B.H., Schreiber, F. (2008) MetaCrop - A detailed database of crop plant metabolism. Nucleic Acids Research, 36, D954-D958.&#xd;&#xa;[5] Junker, A., Hartmann, A., Schreiber, F., B&#xe4;umlein, H. (2010) An engineer&#x27;s view on regulation of seed development. Trends in Plant Science, 15(6), 303-307.&#xd;&#xa

VANTED: A system for advanced data analysis and visualization in the context of biological networks

BACKGROUND: Recent advances with high-throughput methods in life-science research have increased the need for automatized data analysis and visual exploration techniques. Sophisticated bioinformatics tools are essential to deduct biologically meaningful interpretations from the large amount of experimental data, and help to understand biological processes. RESULTS: We present VANTED, a tool for the visualization and analysis of networks with related experimental data. Data from large-scale biochemical experiments is uploaded into the software via a Microsoft Excel-based form. Then it can be mapped on a network that is either drawn with the tool itself, downloaded from the KEGG Pathway database, or imported using standard network exchange formats. Transcript, enzyme, and metabolite data can be presented in the context of their underlying networks, e. g. metabolic pathways or classification hierarchies. Visualization and navigation methods support the visual exploration of the data-enriched networks. Statistical methods allow analysis and comparison of multiple data sets such as different developmental stages or genetically different lines. Correlation networks can be automatically generated from the data and substances can be clustered according to similar behavior over time. As examples, metabolite profiling and enzyme activity data sets have been visualized in different metabolic maps, correlation networks have been generated and similar time patterns detected. Some relationships between different metabolites were discovered which are in close accordance with the literature. CONCLUSION: VANTED greatly helps researchers in the analysis and interpretation of biochemical data, and thus is a useful tool for modern biological research. VANTED as a Java Web Start Application including a user guide and example data sets is available free of charge at

CelticGraph: Drawing Graphs as Celtic Knots and Links

Celtic knots are an ancient art form often attributed to Celtic cultures, used to decorate monuments and manuscripts, and to symbolise eternity and interconnectedness. This paper describes the framework CelticGraph to draw graphs as Celtic knots and links. The drawing process raises interesting combinatorial concepts in the theory of circuits in planar graphs. Further, CelticGraph uses a novel algorithm to represent edges as B\'ezier curves, aiming to show each link as a smooth curve with limited curvature.Comment: Appears in the Proceedings of the 31st International Symposium on Graph Drawing and Network Visualization (GD 2023

HTPheno: An image analysis pipeline for high-throughput plant phenotyping

<p>Abstract</p> <p>Background</p> <p>In the last few years high-throughput analysis methods have become state-of-the-art in the life sciences. One of the latest developments is automated greenhouse systems for high-throughput plant phenotyping. Such systems allow the non-destructive screening of plants over a period of time by means of image acquisition techniques. During such screening different images of each plant are recorded and must be analysed by applying sophisticated image analysis algorithms.</p> <p>Results</p> <p>This paper presents an image analysis pipeline (HTPheno) for high-throughput plant phenotyping. HTPheno is implemented as a plugin for ImageJ, an open source image processing software. It provides the possibility to analyse colour images of plants which are taken in two different views (top view and side view) during a screening. Within the analysis different phenotypical parameters for each plant such as height, width and projected shoot area of the plants are calculated for the duration of the screening. HTPheno is applied to analyse two barley cultivars.</p> <p>Conclusions</p> <p>HTPheno, an open source image analysis pipeline, supplies a flexible and adaptable ImageJ plugin which can be used for automated image analysis in high-throughput plant phenotyping and therefore to derive new biological insights, such as determination of fitness.</p