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| Falko Krause; Timo Lubitz; Marvin Schulz; Edda Klipp. |
| semanticSBML 2.0 is a collection of online services for the processing of biochemical networks in the SBML (Systems Biology Markup Language) document format. It allows users to edit SBO (Systems Biology Ontology) and RDF based MIRIAM (Minimum Information Required in the Annotation of Models) annotations, check for semantic validity, compare and merge SBML documents, and to create submodels. Given an annotated SBML document similar SBML documents can be retrieved from the BioModels Database via a ranked similarity search. Further features of semanticSBML 2.0 include graph visualization of SBML documents, parameter balancing, creation of SBML documents using shorthand SBML, and an interface to the BioModels Database that allows the comparison of document... |
| Tipo: Poster |
Palavras-chave: Bioinformatics; Data Standards. |
| Ano: 2010 |
URL: http://precedings.nature.com/documents/5402/version/1 |
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| Wolfram Liebermeister; Falko Krause; Jannis Uhlendorf; Timo Lubitz; Edda Klipp. |
| Semantic annotations in SBML (systems biology markup language) enable computer programs to check and process biochemical models based on their biochemical meaning. Annotations are an important prerequisite for model merging, which would be a major step towards the construction of large-scale cell models. The software tool semanticSBML allows users to check and edit MIRIAM annotations and SBO terms, the most common forms of annotation in SBML models. It uses a large collection of biochemical names and database identifiers to support modellers in finding the right annotations. Annotated SBML models can also be built from lists of chemical reactions. In model merging, semanticSBML suggests a preliminary merged model based on MIRIAM annotations in the original... |
| Tipo: Poster |
Palavras-chave: Bioinformatics. |
| Ano: 2009 |
URL: http://precedings.nature.com/documents/3093/version/1 |
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| Falko Krause; Wolfram Liebermeister. |
| The BioModels database contains biochemical network models in SBML format, in which the biochemical meaning of elements is specified by MIRIAM-compliant RDF annotations. We used these annotations to define a similarity measure for models, scoring the overlap of the biochemical systems described. Based on this score, we used two-way clustering to detect groups of similar models and groups of co-occuring model elements. To recognize and compare biochemical elements, we used routines from the software semanticSBML. A Python script extracts all MIRIAM annotations (regardless of their qualifiers) using the semanticSBML annotation classes. The result is a matrix in which the rows represent the models (e.g. BioModel 001), while the columns represent specific... |
| Tipo: Poster |
Palavras-chave: Bioinformatics. |
| Ano: 2009 |
URL: http://precedings.nature.com/documents/3444/version/1 |
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