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WsdlDateSoapBindingImpl is a generated part of the INVOKER (in other middleware systems this part is called skeleton or server side stub) that invokes the remote object on server side. WsdlDateSoapBindingStub is a CLIENT PROXY corresponding to the generated INVOKER part to be used on client side. The common interface SimpleDate is used both on client and server side, as it is required for both CLIENT PROXY and INVOKER. SimpleDateService is a factory interface to create instances of SimpleDate. SimpleDateServiceLocator is a concrete factory class for the CLIENT PROXY. It is to be used on client side.

10

OQLQuery query = new OQLQuery(txn) ; query.create("SELECT * " + "FROM intron IN intronExtent " + "WHERE intron.transcribedRegion.chromosome.number = $1"); String number = (String)vec.elementAt(1); query.bind(number); Object result = query.execute();

If WSDL is generated from the deployed service, only the client-side classes need to be generated using the tool WSDL2Java (this can be specified using a command-line option). In other frameworks, such as

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This chapter has described and illustrated the use of object databases in bioinformatics applications It has been argued that object databases contain a range of modeling and programming facilities that makes them suitable for use with complex biological data The two principal weaknesses of the relational model limited modeling facilities and impedance mismatch-prone programming have limited its uptake in bioinformatics, in particular for use in systems that deal with the more complex data sets or that support sophisticated analyses The recent extensions to the relational model, in particular to support abstract data types (also known as data blades or cartridges), allow certain bioinformatics tasks to be supported much more effectively in the database than was previously the case For example, it is possible to envisage a data type sequence for storing protein sequences that supports homology-based sequence comparisons, searching for motifs, and construction of alignments.

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24.09.2004 21:09

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Support for such facilities within the database would allow sequence analysis and other retrieval tasks to be conducted in a much more integrated environment than has traditionally been the case However, the ODMG standard also provides facilities that fit well with current trends in bioinformatics In particular, object-orientation in general is well suited for use with bioinformatics applications; in fact, all of object-oriented design, programming, and middleware are now prominent in research and development activities The close relationship between the ODMG model and models for design, programming, and interoperation of software systems means that ODMG databases can fit in well with existing technologies To date, a significant proportion of the object database activity in bioinformatics has made use of homegrown object models and systems [Gray 1990]; [Durbin 1991]; [Kosky 1998].

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This has limited reuse of ideas, software, interfaces, and experience across the different platforms, and has prevented bioinformatics activities from benefiting from the performance and scalability benefits of commercial products Although several industrial and research projects have made use of commercial object databases, such activities are quite thinly spread over organizations and problems However, the success of ACeDB as a repository for genomic data indicates that object database technology can have a significant impact in bioinformatics Furthermore, the rapidly changing face of bioinformatics, with new kinds of data and analyses in the postgenome sequencing phase, means that the data management challenges presented by bioinformatics applications are by no means on the wane.

Web Services Technology Projection GLUE, the CLIENT PROXY can also be generated on the fly (see the discussion of GLUE on page 281).

Listing 10.3 (continued)

The GIMS object database is currently being used at Manchester University in the UK for conducting analyses over the yeast genome, in particular for relating core sequence data, as described in this chapter, with information on protein-protein interactions [Eilbeck 1999] and transcription levels [Paton 2000] Ongoing work will increase the range of analyses being carried out, and will extend the system to support different kinds of functional genomic data and data relating to organisms other than yeast A public interface to GIMS will be made available in due course from http://imgcsmanacuk/gims..

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