Box 3.5
Two Examples of Well-Curated Data Repositories

GenBank


GenBank is a public database of all known nucleotide and protein sequences, distributed by the National Center for Biotechnology Information (NCBI), a division of the National Library of Medicine (NLM). As of January 2003, GenBank contained over 20 billion nucleotide bases in sequences from more than 55,000 species—human, mice, rat, nematode, fruit fly, and the model plant Arabidopsis are the most represented. GenBank and its collaborating European (EMBL) and Japanese (JPPL) databases are built with data submitted electronically by individual investigators (using BankIt or Sequin submission programs) and large-scale sequencing centers (using batch procedures). Each submission is reviewed for quality assurance and assigned an accession number; sequence updates are designated as new versions. The database is organized by a sequence-based taxonomy into divisions (e.g., bacteria, viruses, primates) and categories (e.g., expressed sequence tags, genome survey sequences, high-throughput genomic data). GenBank makes available derivative databases, for example of putative new genes, from these data.


Investigators use the Entrez retrieval system for cross-database searching of GenBank’s collections of DNA, protein, and genome mapping sequence data, population sets, the NCBI taxonomy, protein structures from the Molecular Modeling Database (MMDB), and MEDLINE references (from the scientific literature). A popular tool is BLAST, the sequence alignment program, for finding GenBank sequences similar to a query sequence. The entire database is available by anonymous FTP in compressed flat-file format, updated every 2 months. NCBI offers its ToolKit to software developers creating their own interfaces and specialized analytical tools.


The Research Resource for Complex Physiologic Signals


The Research Resource for Complex Physiologic Signals was established by the National Center for Research Resources of the National Institutes of Health to support the study of complex biomedical signals. The creation of this three-part resource (PhysioBank, PhysioToolkit, and PhysioNet) overcomes long-standing barriers to hypothesis-testing research in this field by enabling access to validated, standardized data and software.1


PhysioBank comprises databases of multiparameter, cardiopulmonary, neural, and other biomedical signals from healthy subjects and patients with pathologies such as epilepsy, congestive heart failure, sleep apnea, and sudden cardiac death. In addition to fully characterized, multiply reviewed signal data, PhysioBank provides online access to archival data that underpin results reported in the published literature, significantly extending the contribution of that published work. PhysioBank provides theoreticians and software developers with realistic data with which to test new algorithms.


The PhysioToolkit includes software for the detection of physiologically significant events using both classic methods and novel techniques from statistical physics, fractal scaling analysis, and nonlinear dynamics; the analysis of nonstationary processes; interactive display and characterization of signals; the simulation of physiological and other signals; and the quantitative evaluation and comparison of analysis algorithms.


PhysioNet is an online forum for the dissemination and exchange of recorded biomedical signals and the software for analyzing such signals; it provides facilities for the cooperative analysis of data and the evaluation of proposed new algorithms. The database is available at http://www.physionet.org/physiobank.

1  

A.L. Goldberger, L.A. Amaral, L. Glass, J.M. Hausdorff, P.C. Ivanov, R.G. Mark, J.E. Mietus, G.B. Moody, C.K. Peng, and H.E. Stanley, “PhysioBank, PhysioToolkit, and PhysioNet: Components of a New Research Resource for Complex Physiologic Signals,” Circulation 101(23):E215-E220, 2000.



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