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EpiC: A Resource for Integrating Information and Analyses to Enable Selection of Epitopes for Antibody Based Experiments

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Data Integration in the Life Sciences (DILS 2009)

Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 5647))

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Abstract

EpiC is a web resource for choosing epitopes for use in antibody based experiments. It integrates a suite of tools to identify the subsequence of a target protein that a binder interacts with. Where the binder is an antibody this subsequence is termed an epitope, i.e. the region of a protein that an antibody specifically recognises. EpiC is part of the Europe-wide project ProteomeBinders, thats aims to develop a resource of binding molecules for the entire Human Proteome. EpiC has a simple interactive web interface that provides experimentalists with an integrated suite of bioinformatic tools and annotation information. Crucially this neither requires the user to download any specialist software nor develop scripting tools.

Given the diversity of applications for affinity reagents, it is important that the resource provides relevant information dependent on the type of experiment being carried out. It is important to note that researchers often require multiple different binders for one protein and different binders for use in different experiments. EpiC achieves access to these wide range of tools using state of the art methods of data integration. Webservices and REST interfaces such as the Distributed Annotation System are used to deliver the information to the user. These ensure that the latest versions of the analysis software and annotation are displayed to the user, relieving the user of the need to keep up to date with the latest databases and software.

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References

  1. Taussig, M.J., Stoevesandt, O., Borrebaeck, C.A.K., Bradbury, A.R., Cahill, D., Cambillau, C., de Daruvar, A., Dübel, S., Eichler, J., Frank, R., Gibson, T.J., Gloriam, D., Gold, L., Herberg, F.W., Hermjakob, H., Hoheisel, J.D., Joos, T.O., Kallioniemi, O., Koegll, M., Konthur, Z., Korn, B., Kremmer, E., Krobitsch, S., Landegren, U., van der Maarel, S., McCafferty, J., Muyldermans, S., Nygren, P.-r., Palcy, S., Plückthun, A., Polic, B., Przybylski, M., Saviranta, P., Sawyer, A., Sherman, D.J., Skerra, A., Templin, M., Ueffing, M., Uhlén, M.: Proteomebinders: planning a european resource of affinity reagents for analysis of the human proteome. Nature Methods 4(1), 13–17 (2007)

    Article  CAS  PubMed  Google Scholar 

  2. Boutet, E., Lieberherr, D., Tognolli, M., Schneider, M., Bairoch, A.: Uniprotkb/swiss-prot. Methods Mol. Biol. 406, 89–112 (2007)

    CAS  PubMed  Google Scholar 

  3. Zhang, Q., Wang, P., Kim, Y., Haste-Andersen, P., Beaver, J., Bourne, P.E., Bui, H.H., Buus, S., Frankild, S., Greenbaum, J., Lund, O., Lundegaard, C., Nielsen, M., Ponomarenko, J., Sette, A., Zhu, Z., Peters, B.: Immune epitope database analysis resource (IEDB-AR). Nucl. Acids. Res. 36 (July 2008)

    Google Scholar 

  4. Persson, A., Hober, S., Uhlén, M.: A human protein atlas based on antibody proteomics. Curr. Opin. Mol. Ther. 8, 185–190 (2006)

    CAS  PubMed  Google Scholar 

  5. Björling, E., Uhlén, M.: Antibodypedia, a portal for sharing antibody and antigen validation data. Mol. Cell. Proteomics 7, 2028–2037 (2008)

    Article  PubMed  Google Scholar 

  6. Letunic, I., Doerks, T., Bork, P.: Smart 6: recent updates and new developments. Nucl. Acids Res. 37 (January 2009)

    Google Scholar 

  7. Ward, J.J., McGuffin, L.J., Bryson, K., Buxton, B.F., Jones, D.T.: The disopred server for the prediction of protein disorder. Bioinformatics 20, 2138–2139 (2004)

    Article  CAS  PubMed  Google Scholar 

  8. Finn, R.D., Tate, J., Mistry, J., Coggill, P.C., Sammut, S.J., Hotz, H.R., Ceric, G., Forslund, K., Eddy, S.R., Sonnhammer, E.L., Bateman, A.: The pfam protein families database. Nucl. Acids. Res. 36 (January 2008)

    Google Scholar 

  9. Kabsch, W., Sander, C.: Dictionary of protein secondary structure: pattern recognition of hydrogen-bonded and geometrical features. Biopolymers 22, 2577–2637 (1983)

    Article  CAS  PubMed  Google Scholar 

  10. Diella, F., Haslam, N., Chica, C., Budd, A., Michael, S., Brown, N.P., Trave, G., Gibson, T.J.: Understanding eukaryotic linear motifs and their role in cell signaling and regulation. Front. Biosci. 13, 6580–6603 (2008)

    Article  CAS  PubMed  Google Scholar 

  11. Lopez, R., Silventoinen, V., Robinson, S., Kibria, A., Gish, W.: Wu-blast2 server at the european bioinformatics institute. Nucl. Acids Res. 31, 3795–3798 (2003)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Zamboulis, L., Fan, H., Belhajjame, K., Siepen, J., Jones, A., Martin, N., Poulovassilis, A., Hubbard, S., Embury, S., Paton, N.: Data access and integration in the iSpider proteomics grid. In: Leser, U., Naumann, F., Eckman, B. (eds.) DILS 2006. LNCS (LNBI), vol. 4075, pp. 3–18. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

  13. Labarga, A., Valentin, F., Anderson, M., Lopez, R.: Web services at the european bioinformatics institute. Nucl. Acids Res. 35 (July 2007)

    Google Scholar 

  14. Oinn, T., Addis, M., Ferris, J., Marvin, D., Senger, M., Greenwood, M., Carver, T., Glover, K., Pocock, M.R., Wipat, A., Li, P.: Taverna: a tool for the composition and enactment of bioinformatics workflows. Bioinformatics 20, 3045–3054 (2004)

    Article  CAS  PubMed  Google Scholar 

  15. Jenkinson, A., Albrecht, M., Birney, E., Blankenburg, H., Down, T., Finn, R., Hermjakob, H., Hubbard, T., Jimenez, R., Jones, P., Kahari, A., Kulesha, E., Macias, J., Reeves, G., Prlic, A.: Integrating biological data - the distributed annotation system. BMC Bioinformatics 9(suppl. 8) (2008)

    Google Scholar 

  16. Rice, P., Longden, I., Bleasby, A.: Emboss: The european molecular biology open software suite. Trends Genet. 16, 276–277 (2000)

    Article  CAS  PubMed  Google Scholar 

  17. Cote, R., Jones, P., Martens, L., Kerrien, S., Reisinger, F., Lin, Q., Leinonen, R., Apweiler, R., Hermjakob, H.: The Protein Identifier Cross-Reference (PICR) service: reconciling protein identifiers across multiple source databases. BMC Bioinformatics 8(1) (2007)

    Google Scholar 

  18. Jimenez, R.C.C., Quinn, A.F.F., Garcia, A., Labarga, A., O’Neill, K., Martinez, F., Salazar, G.A.A., Hermjakob, H.: Dasty2, an Ajax protein DAS client. Bioinformatics (August 2008)

    Google Scholar 

  19. Orchard, S., Montechi-Palazzi, L., Deutsch, E.W., Binz, P.A., Jones, A.R., Paton, N., Pizarro, A., Creasy, D.M., Wojcik, J., Hermjakob, H.: Five years of progress in the standardization of proteomics data. In: 4th annual spring workshop of the HUPO-Proteomics Standards Initiative. Ecole Nationale Supérieure (ENS). Proteomics, Lyon, France, April 23-25, vol. 7, pp. 3436–3440 (October 2007)

    Google Scholar 

  20. Côté, R.G.G., Jones, P., Martens, L., Apweiler, R., Hermjakob, H.: The ontology lookup service: more data and better tools for controlled vocabulary queries. Nucl. Acids Res. (May 2008)

    Google Scholar 

  21. Bendtsen, J.D., Nielsen, H., von Heijne, G., Brunak, S.: Improved prediction of signal peptides: Signalp 3.0. J. Mol. Biol. 340, 783–795 (2004)

    Article  PubMed  Google Scholar 

  22. Julenius, K., Mølgaard, A., Gupta, R., Brunak, S.: Prediction, conservation analysis, and structural characterization of mammalian mucin-type o-glycosylation sites. Glycobiology 15, 153–164 (2005)

    Article  CAS  PubMed  Google Scholar 

  23. Gnad, F., Ren, S., Cox, J., Olsen, J., Macek, B., Oroshi, M., Mann, M.: Phosida (phosphorylation site database): management, structural and evolutionary investigation, and prediction of phosphosites. Genome Biology 8(11) (2007)

    Google Scholar 

  24. Juretić, D., Zoranić, L., Zucić, D.: Basic charge clusters and predictions of membrane protein topology. J. Chem. Inf. Comput. Sci. 42(3), 620–632 (2002)

    Article  PubMed  Google Scholar 

  25. Käll, L., Krogh, A., Sonnhammer, E.L.: Advantages of combined transmembrane topology and signal peptide prediction–the phobius web server. Nucl. Acids. Res. 35 (July 2007)

    Google Scholar 

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Authors and Affiliations

  1. Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany

    Niall Haslam & Toby Gibson

Authors
  1. Niall Haslam
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  2. Toby Gibson
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Editors and Affiliations

  1. School of Computer Science, University of Manchester, M13 9PL, Manchester, UK

    Norman W. Paton  & Paolo Missier  & 

  2. School of Computer Science, The University of Manchester, Oxford Road, M13 9PL, Manchester, UK

    Cornelia Hedeler

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Haslam, N., Gibson, T. (2009). EpiC: A Resource for Integrating Information and Analyses to Enable Selection of Epitopes for Antibody Based Experiments. In: Paton, N.W., Missier, P., Hedeler, C. (eds) Data Integration in the Life Sciences. DILS 2009. Lecture Notes in Computer Science(), vol 5647. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02879-3_14

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  • DOI: https://doi.org/10.1007/978-3-642-02879-3_14

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-02878-6

  • Online ISBN: 978-3-642-02879-3

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