Propagating semantic information in biochemical network models

BackgroundTo enable automatic searches, alignments, and model combination, the elements of systems biology models need to be compared and matched across models. Elements can be identified by machine-readable biological annotations, but assigning such annotations and matching non-annotated elements is tedious work and calls for automation.ResultsA new method called "semantic propagation" allows the comparison of model elements based not only on their own annotations, but also on annotations of surrounding elements in the network. One may either propagate feature vectors, describing the annotations of individual elements, or quantitative similarities between elements from different models. Based on semantic propagation, we align partially annotated models and find annotations for non-annotated model elements.ConclusionsSemantic propagation and model alignment are included in the open-source library semanticSBML, available on sourceforge. Online services for model alignment and for annotation prediction can be used at http://www.semanticsbml.org.

[1]  E. Klipp,et al.  Retrieval, alignment, and clustering of computational models based on semantic annotations , 2011, Molecular systems biology.

[2]  Luigi Palopoli,et al.  Biological Network Querying Techniques: Analysis and Comparison , 2011, J. Comput. Biol..

[3]  Y.-H. Huang,et al.  PINT: Pathways INtegration Tool , 2010, Nucleic Acids Res..

[4]  Ela Hunt,et al.  Biochemical network matching and composition , 2010, EDBT '10.

[5]  Jacky L. Snoep,et al.  BioModels Database: a free, centralized database of curated, published, quantitative kinetic models of biochemical and cellular systems , 2005, Nucleic Acids Res..

[6]  Ilias Maglogiannis,et al.  KEGGconverter: a tool for the in-silico modelling of metabolic networks of the KEGG Pathways database , 2009, BMC Bioinformatics.

[7]  M. Kanehisa,et al.  Development of a chemical structure comparison method for integrated analysis of chemical and genomic information in the metabolic pathways. , 2003, Journal of the American Chemical Society.

[8]  Sebastian Wernicke,et al.  Simple and Fast Alignment of Metabolic Pathways by Exploiting Local Diversity , 2007, APBC.

[9]  Hugh D. Spence,et al.  Minimum information requested in the annotation of biochemical models (MIRIAM) , 2005, Nature Biotechnology.

[10]  Hideo Matsuda,et al.  A Multiple Alignment Algorithm for Metabolic Pathway Analysis Using Enzyme Hierarchy , 2000, ISMB.

[11]  Hiroaki Kitano,et al.  The systems biology markup language (SBML): a medium for representation and exchange of biochemical network models , 2003, Bioinform..

[12]  Angel Rubio,et al.  Correlation between gene expression and GO semantic similarity , 2005, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

[13]  Carole A. Goble,et al.  Investigating Semantic Similarity Measures Across the Gene Ontology: The Relationship Between Sequence and Annotation , 2003, Bioinform..

[14]  Edda Klipp,et al.  Annotation and merging of SBML models with semanticSBML , 2010, Bioinform..

[15]  Yoshihiro Yamanishi,et al.  KEGG for linking genomes to life and the environment , 2007, Nucleic Acids Res..

[16]  BMC Bioinformatics , 2005 .

[17]  Ron Y. Pinter,et al.  Alignment of metabolic pathways , 2005, Bioinform..

[18]  J. Becker,et al.  Topic-based Vector Space Model , 2003 .

[19]  François Fages,et al.  A graphical method for reducing and relating models in systems biology , 2010, Bioinform..

[20]  Clifford A. Shaffer,et al.  Model aggregation: a building-block approach to creating large macromolecular regulatory networks , 2009, Bioinform..

[21]  F. Hynne,et al.  Full-scale model of glycolysis in Saccharomyces cerevisiae. , 2001, Biophysical chemistry.

[22]  Jehoshua Bruck,et al.  Scaffold proteins may biphasically affect the levels of mitogen-activated protein kinase signaling and reduce its threshold properties. , 2000, Proceedings of the National Academy of Sciences of the United States of America.

[23]  Mona Singh,et al.  Whole-proteome prediction of protein function via graph-theoretic analysis of interaction maps , 2005, ISMB.

[24]  Roded Sharan,et al.  QPath: a method for querying pathways in a protein-protein interaction network , 2006, BMC Bioinformatics.

[25]  Sing-Hoi Sze,et al.  Path Matching and Graph Matching in Biological Networks , 2007, J. Comput. Biol..

[26]  Roded Sharan,et al.  QNet: A Tool for Querying Protein Interaction Networks , 2007, RECOMB.

[27]  Chi-Ying F. Huang,et al.  Ultrasensitivity in the mitogen-activated protein kinase cascade. , 1996, Proceedings of the National Academy of Sciences of the United States of America.

[28]  Roded Sharan,et al.  PathBLAST: a tool for alignment of protein interaction networks , 2004, Nucleic Acids Res..

[29]  Bonnie Berger,et al.  Global alignment of multiple protein interaction networks with application to functional orthology detection , 2008, Proceedings of the National Academy of Sciences.

[30]  Gerard Salton,et al.  The SMART Retrieval System—Experiments in Automatic Document Processing , 1971 .

[31]  Björn Olsson,et al.  GOSAP: Gene Ontology-Based Semantic Alignment of Biological Pathways , 2008, Int. J. Bioinform. Res. Appl..

[32]  Edda Klipp,et al.  SBMLmerge, a system for combining biochemical network models. , 2006, Genome informatics. International Conference on Genome Informatics.

[33]  Michael Darsow,et al.  ChEBI: a database and ontology for chemical entities of biological interest , 2007, Nucleic Acids Res..