Bio-medical Ontologies Maintenance and Change Management

A Summary of Genomic Databases: Overview and Discussion 47
sets of words, also combining them by logical operators. Such keywords are to
be searched for in specific and not a-priori determined fields and tables of the
database. With forms, searching starts by specifying the values to look for
that are associated to attributes of the database. Multi-attributes searches
can be obtained by combining the sub-queries by logical operators. As an
example, ArkDB [1] supports both free text and forms queries.
Graphical interaction based methods are also quite common in genomic
database access systems. In fact, a large set of genomic information can be
visualized by physical and genetic maps, whereby queries can be formulated
by interacting with graphical objects representing the annotated genomic
data. Graphical support tools have been indeed developed such as, e.g., the
GenericGenomeBrowser(GBrowser)[48], which allows the user to navigate
interactively through a genome sequence, to select specific regions and to
recover the correspondent annotations and information. Databases such as
CADRE [7] and HCVDB [17], for example, allow the user to query their
repository by graphical interaction.
Sequence based queries rely on the computation of similarity among genomic
sequences and patterns. In this case, the input is a nucleotides or
amino-acid sequence and data mining algorithms, such as in [29], are exploited
to process the query, so that alignments and similar information are
retrieved and returned.
Query language based methods exploit DBMS-native query languages
(e.g., SQL-based ones), allowing a “low level” interaction with the databases.
At the moment, few databases (WormBase [28] and GrainGenes [15])
support them.
2.5 Result Formats
In genomic databases, several formats are adopted to represent query results.
Web interfaces usually provide answers encoded in HTML, but other formats
are often available as well. In the following discussion, we shall refer to the
formats adopted for representing query results and not to those used for
ftp-downloadable data.
Flat files are semi-structured text files where each information class is reported
on one or more than one consecutive lines, identified by a code used
to characterize the annotated attributes. The most common flat files formats
are the GenBankFlatFile(GBFF)[41] and the European Molecular Biology
Laboratory Data Library Format [44]. These formats represent basically the
same information contents, even if with some syntactic differences. Databases
supporting the GenBank Flat File are, for example, CADRE [7] and Ensembl
[13], whereas databases supporting the EMBL format are CADRE [7], Ensembl
[13], and ToxoDB [37].
The comma/tab and the attribute-value separated files are similar to flat
files, but featuring some mildly stronger form of structure. The former
ones, supported for example by BioCyc [4], TAIR [46] and HumanCyc [18],