=Paper= {{Paper |id=Vol-1515/poster7 |storemode=property |title=ChEBI for systems biology and metabolic modelling |pdfUrl=https://ceur-ws.org/Vol-1515/poster7.pdf |volume=Vol-1515 |dblpUrl=https://dblp.org/rec/conf/icbo/HastingsSMKDOTM15 }} ==ChEBI for systems biology and metabolic modelling== https://ceur-ws.org/Vol-1515/poster7.pdf
               ChEBI for systems biology and metabolic modelling
          Janna Hastings1,* Neil Swainston2, Venkatesh Muthukrishnan1, Namrata Kale1,
     Adriano Dekker1, Gareth Owen1, Steve Turner1, Pedro Mendes2 and Christoph Steinbeck1
      1
          Cheminformatics and Metabolism, EMBL -- European Bioinformatics Institute (EMBL-EBI), Hinxton, UK
           2
             Manchester Institute of Biotechnology, School of Computer Science, University of Manchester, UK



                                                                    ChEBI will be providing a facility for bulk submission of
1   INTRODUCTION                                                    novel compounds which will be automatically classified
ChEBI (http://www.ebi.ac.uk/chebi) is a curated database            within the ontology. We will also be undertaking curation of
and ontology of biologically relevant small molecules. It is        the known metabolomes (i.e. all the known metabolites)
widely used as a reference for chemicals in the context of          across four major species (human, mouse, E. coli and yeast).
biological data such as protein interactions, pathways, and         Finally, we will be introducing into the ChEBI public web-
models (Hastings et al., 2013). As of the last release (May         site novel visualisations of relevance to the systems biology
2015), ChEBI contains 44,263 fully curated entries, each of         community, such as chemicals in the context of pathways
which is classified within one of the sub-ontologies: chemi-        (powered by Reactome, Croft et al., 2011, and
cal entities (classified according to structural features), roles   MetaboLights, Haug et al., 2013) and models (powered by
(classified according to biological or chemical mode of ac-         BioModels, Li et al., 2010).
tion or use in application), and subatomic particles.
Systems biology brings together a wide range of infor-              ACKNOWLEDGEMENTS
mation about cells, genes and proteins, as well as the small        ChEBI is funded by the BBSRC, grant agreement number
molecules that act on and within these biological structures.       BB/K019783/1 within the “Bioinformatics and biological
It gives a holistic perspective aiming to track and eventually      resources” fund.
simulate the entire functioning of biological systems. One
aspect of systems biology is metabolic modelling, which             REFERENCES
aims to develop metabolic reconstructions. At the whole-            Croft D, O'Kelly G, Wu G, Haw R, et al. (2011) Reactome: a database of
genome scale, these are all-encompassing interlinked maps                  reactions, pathways and biological processes. Nucleic Acids Res.
of all known metabolic reaction pathways for a given organ-                39:D691-7.
ism (Thiele et al., 2013). Chemical data from ChEBI, such           Hastings J., de Matos P., Dekker A., Ennis M., Harsha B., Kale N., Mu-
as molecular formula, chemical structure and ontology rela-                thukrishnan V., Owen G., Turner S., Williams M. and Steinbeck C.
tionships, can fruitfully be used in the model building and                (2013) The ChEBI reference database and ontology for biologically
refining process to improve model accuracy and enhance the                 relevant chemistry: enhancements for 2013. Nucleic Acids Res.
representation of metabolism (Swainston et al., 2011).                     41:D456-63.
Within this context, efforts are currently underway to im-          Haug, K., Salek, R. M., Conesa, P., Hastings, J. et al. (2013)
prove ChEBI for systems biology and metabolic modelling.                   MetaboLights—an open-access general-purpose repository for
The enhancements include the addition of a library, lib-                   metabolomics studies and associated metadata. Nucl. Acids Res. 41:
ChEBI, for comprehensive programmatic access to ChEBI                      D781-D786.
data, which will be widely applicable but with a particular         Li, C., Donizelli, M., Rodriguez, N., Dharuri H. et al. (2010) BioModels
focus on metabolic modelling. It will include the facility to              Database: An enhanced, curated and annotated resource for pub-
determine relationships between molecules, such as stereo-                 lished quantitative kinetic models. BMC Systems Biology 4:92.
chemistry, tautometrism and redox pairings, to calculate            Swainston N, Mendes P, et al. (2011) The SuBliMinaL Toolbox: automat-
important physicochemical properties, such as pKa and the                  ing steps in the reconstruction of metabolic networks. Journal of In-
Gibbs free energy of formation, and to harness these facili-               tegrative Bioinformatics, 8(2):186
ties in support of developing, merging and expanding meta-          Thiele, I., Swainston, N., Fleming, R.M.T, et al. (2013) A community-
bolic models. The library will be open source, available in                driven global reconstruction of human metabolism. Nature Biotech-
several programming languages including Java and Python.                   nology 31, 419–425.




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