Databases and Systems

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methods of integrating maps in the erstwhile human Genome Database (GDB).
Cooper et al describe their database of human mutations, an early entry in the
increasingly important field of variation databases.
The article by Nadkarni et al provides a link to the developing field of
neuroinformatics, which is concerned with databases of such neuroscience data such
as structural (MR or CT) or functional (PET, fMRI) images of the brain, histological
slices, EEG and MEG data, cellular and network models, single cell recordings, and
so on. [15]. This article is included not only as a representative of neuroinformatic
work, but because it is one of the few current neuroinformatics efforts that links the
molecular scale of bioinformatics to the neurophysiological scale, since it addresses
the physiology of olfaction from the receptor sequences up to cellular and network
physiology.
Eppig et al describe the Mouse Genome Database (MGD) and its companion
system, the mouse Gene Expression Database (GXD). One of the key challenges for
the next generation of databases is to begin to span the levels of organization between
genotype and phenotype, where the processes of development and physiology reside.
Baldock et al describe an anatomical atlas of the mouse suitable for representing
spatiotemporal patterns of gene expression; the Edinburgh (Baldock et al) and
Jackson Laboratory (Eppig et al) projects are collaborating to link the genetic and
spatial databases together. The plant kingdom, which has recently experienced a
rapid acceleration of genomic scrutiny in both the private and public sectors, is
represented in articles on MaizeDB by Polacco and Coe and on the USDA’s
Agricultural Genome Information System by Beckstrom-Sternberg and Jamison.
Gelbart et al describe the rich integration of genomic and phenotypic data on
Drosophila in Flybase. Mary Berlyn describes the E.coli Genetic Stock Center
Database, which provides query-by-genotype access to the stock center’s extensive
collection of mutant strains.
The Software section contains a number of articles that address one or
another aspect of the problem of integrating data from heterogenous sources. There
are two common ways to achieve such integration: federation, in which the data
continue to reside in separate databases but a software layer makes them act as a
single integrated collection, and physical integration, often called warehousing, in
which the data are combined into a single repository for querying purposes. Both
approaches involve transforming the data into a common format; federation does the
transformation at query time, whereas warehousing does it as a preprocessing step.
One consequence of this difference is that warehouses are more difficult to keep
current as the underlying databases are updated. The choice of federation vs.
warehousing has performance implications as well, though they are not always easy
to predict. A warehouse can map in a straightforward way to a DBMS product, and
make full use of the tuning and optimization capabilities of that product. Federated
systems must pay the price of translating queries at run-time, possibly doing
unoptimized distributed joins of query fragments across multiple databases, and
converting data into the standard form. It is also possible for federated systems to