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The future of biocuration

Author

Listed:
  • Doug Howe

    (The Zebrafish Information Network, 5291 University of Oregon)

  • Maria Costanzo

    (Saccharomyces and Candida Genome Databases, Stanford University)

  • Petra Fey

    (dictyBase, Northwestern University Biomedical Informatics Center)

  • Takashi Gojobori

    (Centre for Information Biology and DNA Data Bank of Japan, National Institute of Genetics, Research Organization of Information and Systems)

  • Linda Hannick

    (J. Craig Venter Institute, Applied Bioinformatics)

  • Winston Hide

    (South African National Bioinformatics Institute, University of the Western Cape, Private Bag X17
    Harvard School of Public Health)

  • David P. Hill

    (Mouse Genome Informatics, The Jackson Laboratory, Bar Harbor)

  • Renate Kania

    (Scientific Databases and Visualization, EML Research GmbH, Villa Bosch, Schloss-Wolfsbrunnenweg 33)

  • Mary Schaeffer

    (University of Missouri
    Plant Genetics Research Unit, Agricultural Research Service)

  • Susan St Pierre

    (FlyBase, Harvard University)

  • Simon Twigger

    (Rat Genome Database, Bioinformatics Research Center, Medical College of Wisconsin)

  • Owen White

    (Institute for Genome Sciences, University of Maryland School of Medicine)

  • Seung Yon Rhee

    (The Arabidopsis Information Resource, Carnegie Institution for Science)

Abstract

To thrive, the field that links biologists and their data urgently needs structure, recognition and support.

Suggested Citation

  • Doug Howe & Maria Costanzo & Petra Fey & Takashi Gojobori & Linda Hannick & Winston Hide & David P. Hill & Renate Kania & Mary Schaeffer & Susan St Pierre & Simon Twigger & Owen White & Seung Yon Rhee, 2008. "The future of biocuration," Nature, Nature, vol. 455(7209), pages 47-50, September.
    • Handle: RePEc:nat:nature:v:455:y:2008:i:7209:d:10.1038_455047a
    DOI: 10.1038/455047a
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    Citations

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    Cited by:

    1. Liu Yinbin & Zhang Xiaoyue, 2021. "Research on the Overall Architecture and Application of E-Sports Big Data," International Journal of Business and Management, Canadian Center of Science and Education, vol. 15(12), pages 116-116, July.
    2. Carbone, Anna & Jensen, Meiko & Sato, Aki-Hiro, 2016. "Challenges in data science: a complex systems perspective," Chaos, Solitons & Fractals, Elsevier, vol. 90(C), pages 1-7.
    3. Kertcher, Zack & Venkatraman, Rohan & Coslor, Erica, 2020. "Pleasingly parallel: Early cross-disciplinary work for innovation diffusion across boundaries in grid computing," Journal of Business Research, Elsevier, vol. 116(C), pages 581-594.
    4. Renchu Guan & Chen Yang & Maurizio Marchese & Yanchun Liang & Xiaohu Shi, 2014. "Full Text Clustering and Relationship Network Analysis of Biomedical Publications," PLOS ONE, Public Library of Science, vol. 9(9), pages 1-9, September.
    5. Gheorghe MILITARU & Massimo POLLIFRONI & Alexandra IOANID, 2015. "Big Data In Supply Chain Management: An Exploratory Study," Network Intelligence Studies, Romanian Foundation for Business Intelligence, Editorial Department, issue 6, pages 103-108, December.
    6. Vivek Kumar Singh & Sumit Kumar Banshal & Khushboo Singhal & Ashraf Uddin, 2015. "Scientometric mapping of research on ‘Big Data’," Scientometrics, Springer;Akadémiai Kiadó, vol. 105(2), pages 727-741, November.
    7. Michael Marcinkowski, 2016. "Data, ideology, and the developing critical program of social informatics," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 67(5), pages 1266-1275, May.
    8. Stieglitz, Stefan & Mirbabaie, Milad & Ross, Björn & Neuberger, Christoph, 2018. "Social media analytics – Challenges in topic discovery, data collection, and data preparation," International Journal of Information Management, Elsevier, vol. 39(C), pages 156-168.
    9. Hayda Almeida & Marie-Jean Meurs & Leila Kosseim & Greg Butler & Adrian Tsang, 2014. "Machine Learning for Biomedical Literature Triage," PLOS ONE, Public Library of Science, vol. 9(12), pages 1-21, December.
    10. Ekaansh Khosla & Ramesh Dharavath & Rashmi Priya, 2020. "Crop yield prediction using aggregated rainfall-based modular artificial neural networks and support vector regression," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 22(6), pages 5687-5708, August.
    11. Hong-Jie Dai & Johnny Chi-Yang Wu & Richard Tzong-Han Tsai, 2013. "Collective Instance-Level Gene Normalization on the IGN Corpus," PLOS ONE, Public Library of Science, vol. 8(11), pages 1-10, November.
    12. Harley, Diane & Acord, Sophia Krzys, 2011. "Peer Review in Academic Promotion and Publishing: Its Meaning, Locus, and Future," University of California at Berkeley, Center for Studies in Higher Education qt1xv148c8, Center for Studies in Higher Education, UC Berkeley.
    13. Sabrina de Azevedo Silveira & Raquel Cardoso de Melo-Minardi & Carlos Henrique da Silveira & Marcelo Matos Santoro & Wagner Meira Jr, 2014. "ENZYMAP: Exploiting Protein Annotation for Modeling and Predicting EC Number Changes in UniProt/Swiss-Prot," PLOS ONE, Public Library of Science, vol. 9(2), pages 1-12, February.
    14. Řezník, T. & Lukas, V. & Charvát, K. & Horáková, Š. & Charvát junior, K., 2015. "Towards Farm-Oriented Open Data in Europe: the Scope and Pilots of the European Project "FOODIE"," AGRIS on-line Papers in Economics and Informatics, Czech University of Life Sciences Prague, Faculty of Economics and Management, vol. 7(1), pages 1-8, March.
    15. Perrons, Robert K. & McAuley, Derek, 2015. "The case for “n«all”: Why the Big Data revolution will probably happen differently in the mining sector," Resources Policy, Elsevier, vol. 46(P2), pages 234-238.

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