Towards a consensus on datasets and evaluation metrics for developing B-cell epitope prediction tools

Jason A. Greenbaum, Pernille Andersen, Martin Blythe, Huynh-Hoa Bui, Raul E. Cachau, James Crowe, Matthew Davies, A. S. Kolaskar, Ole Lund, Sherrie Morrison, Brendan Mumey, Yanay Ofran, Jean-Luc Pellequer, Clemencia Pinilla, Julia V. Ponomarenko, G. P. S. Raghava, Marc H. van Regenmortel, Erwin L. Roggen, Alessandro Sette, Avner Schlessinger & 3 others Johannes Sollner, Martin Zand, Bjoern Peters

    Research output: Contribution to journalJournal articleResearchpeer-review

    Abstract

    A B-cell epitope is the three-dimensional structure within an antigen that can be bound to the variable region of an antibody. The prediction of B-cell epitopes is highly desirable for various immunological applications, but has presented a set of unique challenges to the bioinformatics and immunology communities. Improving the accuracy of B-cell epitope prediction methods depends on a community consensus on the data and metrics utilized to develop and evaluate such tools. A workshop, sponsored by the National Institute of Allergy and Infectious Disease (NIAID), was recently held in Washington, DC to discuss the current state of the B-cell epitope prediction field. Many of the currently available tools were surveyed and a set of recommendations was devised to facilitate improvements in the currently existing tools and to expedite future tool development. An underlying theme of the recommendations put forth by the panel is increased collaboration among research groups. By developing common datasets, standardized data formats, and the means with which to consolidate information, we hope to greatly enhance the development of B-cell epitope prediction tools. (c) 2007 John Wiley & Sons, Ltd.
    Original languageEnglish
    JournalJournal of Molecular Recognition
    Issue number2
    Pages (from-to)75-82
    ISSN0952-3499
    DOIs
    Publication statusPublished - 2007

    Cite this

    Greenbaum, J. A., Andersen, P., Blythe, M., Bui, H-H., Cachau, R. E., Crowe, J., ... Peters, B. (2007). Towards a consensus on datasets and evaluation metrics for developing B-cell epitope prediction tools. Journal of Molecular Recognition, (2), 75-82. https://doi.org/10.1002/jmr.815
    Greenbaum, Jason A. ; Andersen, Pernille ; Blythe, Martin ; Bui, Huynh-Hoa ; Cachau, Raul E. ; Crowe, James ; Davies, Matthew ; Kolaskar, A. S. ; Lund, Ole ; Morrison, Sherrie ; Mumey, Brendan ; Ofran, Yanay ; Pellequer, Jean-Luc ; Pinilla, Clemencia ; Ponomarenko, Julia V. ; Raghava, G. P. S. ; van Regenmortel, Marc H. ; Roggen, Erwin L. ; Sette, Alessandro ; Schlessinger, Avner ; Sollner, Johannes ; Zand, Martin ; Peters, Bjoern. / Towards a consensus on datasets and evaluation metrics for developing B-cell epitope prediction tools. In: Journal of Molecular Recognition. 2007 ; No. 2. pp. 75-82.
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    title = "Towards a consensus on datasets and evaluation metrics for developing B-cell epitope prediction tools",
    abstract = "A B-cell epitope is the three-dimensional structure within an antigen that can be bound to the variable region of an antibody. The prediction of B-cell epitopes is highly desirable for various immunological applications, but has presented a set of unique challenges to the bioinformatics and immunology communities. Improving the accuracy of B-cell epitope prediction methods depends on a community consensus on the data and metrics utilized to develop and evaluate such tools. A workshop, sponsored by the National Institute of Allergy and Infectious Disease (NIAID), was recently held in Washington, DC to discuss the current state of the B-cell epitope prediction field. Many of the currently available tools were surveyed and a set of recommendations was devised to facilitate improvements in the currently existing tools and to expedite future tool development. An underlying theme of the recommendations put forth by the panel is increased collaboration among research groups. By developing common datasets, standardized data formats, and the means with which to consolidate information, we hope to greatly enhance the development of B-cell epitope prediction tools. (c) 2007 John Wiley & Sons, Ltd.",
    author = "Greenbaum, {Jason A.} and Pernille Andersen and Martin Blythe and Huynh-Hoa Bui and Cachau, {Raul E.} and James Crowe and Matthew Davies and Kolaskar, {A. S.} and Ole Lund and Sherrie Morrison and Brendan Mumey and Yanay Ofran and Jean-Luc Pellequer and Clemencia Pinilla and Ponomarenko, {Julia V.} and Raghava, {G. P. S.} and {van Regenmortel}, {Marc H.} and Roggen, {Erwin L.} and Alessandro Sette and Avner Schlessinger and Johannes Sollner and Martin Zand and Bjoern Peters",
    year = "2007",
    doi = "10.1002/jmr.815",
    language = "English",
    pages = "75--82",
    journal = "Journal of Molecular Recognition",
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    Greenbaum, JA, Andersen, P, Blythe, M, Bui, H-H, Cachau, RE, Crowe, J, Davies, M, Kolaskar, AS, Lund, O, Morrison, S, Mumey, B, Ofran, Y, Pellequer, J-L, Pinilla, C, Ponomarenko, JV, Raghava, GPS, van Regenmortel, MH, Roggen, EL, Sette, A, Schlessinger, A, Sollner, J, Zand, M & Peters, B 2007, 'Towards a consensus on datasets and evaluation metrics for developing B-cell epitope prediction tools', Journal of Molecular Recognition, no. 2, pp. 75-82. https://doi.org/10.1002/jmr.815

    Towards a consensus on datasets and evaluation metrics for developing B-cell epitope prediction tools. / Greenbaum, Jason A.; Andersen, Pernille; Blythe, Martin; Bui, Huynh-Hoa; Cachau, Raul E.; Crowe, James; Davies, Matthew; Kolaskar, A. S.; Lund, Ole; Morrison, Sherrie; Mumey, Brendan; Ofran, Yanay; Pellequer, Jean-Luc; Pinilla, Clemencia; Ponomarenko, Julia V.; Raghava, G. P. S.; van Regenmortel, Marc H.; Roggen, Erwin L.; Sette, Alessandro; Schlessinger, Avner; Sollner, Johannes; Zand, Martin; Peters, Bjoern.

    In: Journal of Molecular Recognition, No. 2, 2007, p. 75-82.

    Research output: Contribution to journalJournal articleResearchpeer-review

    TY - JOUR

    T1 - Towards a consensus on datasets and evaluation metrics for developing B-cell epitope prediction tools

    AU - Greenbaum, Jason A.

    AU - Andersen, Pernille

    AU - Blythe, Martin

    AU - Bui, Huynh-Hoa

    AU - Cachau, Raul E.

    AU - Crowe, James

    AU - Davies, Matthew

    AU - Kolaskar, A. S.

    AU - Lund, Ole

    AU - Morrison, Sherrie

    AU - Mumey, Brendan

    AU - Ofran, Yanay

    AU - Pellequer, Jean-Luc

    AU - Pinilla, Clemencia

    AU - Ponomarenko, Julia V.

    AU - Raghava, G. P. S.

    AU - van Regenmortel, Marc H.

    AU - Roggen, Erwin L.

    AU - Sette, Alessandro

    AU - Schlessinger, Avner

    AU - Sollner, Johannes

    AU - Zand, Martin

    AU - Peters, Bjoern

    PY - 2007

    Y1 - 2007

    N2 - A B-cell epitope is the three-dimensional structure within an antigen that can be bound to the variable region of an antibody. The prediction of B-cell epitopes is highly desirable for various immunological applications, but has presented a set of unique challenges to the bioinformatics and immunology communities. Improving the accuracy of B-cell epitope prediction methods depends on a community consensus on the data and metrics utilized to develop and evaluate such tools. A workshop, sponsored by the National Institute of Allergy and Infectious Disease (NIAID), was recently held in Washington, DC to discuss the current state of the B-cell epitope prediction field. Many of the currently available tools were surveyed and a set of recommendations was devised to facilitate improvements in the currently existing tools and to expedite future tool development. An underlying theme of the recommendations put forth by the panel is increased collaboration among research groups. By developing common datasets, standardized data formats, and the means with which to consolidate information, we hope to greatly enhance the development of B-cell epitope prediction tools. (c) 2007 John Wiley & Sons, Ltd.

    AB - A B-cell epitope is the three-dimensional structure within an antigen that can be bound to the variable region of an antibody. The prediction of B-cell epitopes is highly desirable for various immunological applications, but has presented a set of unique challenges to the bioinformatics and immunology communities. Improving the accuracy of B-cell epitope prediction methods depends on a community consensus on the data and metrics utilized to develop and evaluate such tools. A workshop, sponsored by the National Institute of Allergy and Infectious Disease (NIAID), was recently held in Washington, DC to discuss the current state of the B-cell epitope prediction field. Many of the currently available tools were surveyed and a set of recommendations was devised to facilitate improvements in the currently existing tools and to expedite future tool development. An underlying theme of the recommendations put forth by the panel is increased collaboration among research groups. By developing common datasets, standardized data formats, and the means with which to consolidate information, we hope to greatly enhance the development of B-cell epitope prediction tools. (c) 2007 John Wiley & Sons, Ltd.

    U2 - 10.1002/jmr.815

    DO - 10.1002/jmr.815

    M3 - Journal article

    SP - 75

    EP - 82

    JO - Journal of Molecular Recognition

    JF - Journal of Molecular Recognition

    SN - 0952-3499

    IS - 2

    ER -