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Correspondence
Nature 447, 142 (10 May 2007) | doi:10.1038/447142a; Published online 9 May 2007
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Senior Computational Scientist
- Argonne National Laboratory
- Argonne, IL, United States
Faculty Positions
- University of Texas Medical Branch
- Galveston, TX United States
Structured digital abstract makes text mining easy
Mark Gerstein1,2, Michael Seringhaus2 & Stanley Fields3
- Program in Computational Biology and Bioinformatics, Yale University, PO Box 208114, New Haven, Connecticut 06520-8114, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, PO Box 208114, New Haven, Connecticut 06520-8114, USA
- Howard Hughes Medical Institute and Departments of Genome Sciences and Medicine, University of Washington, Box 355065, Seattle, Washington 98195, USA
Your Editorial "The database revolution" (Nature 445, 229–230; doi:10.1038/445229b 2007) highlighted the difficulty in maintaining a stable information architecture for biology — in terms of both funding it consistently and evolving a common format.
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