The Semantic community should work toward a possible agreement of using an explicit identification system that could help unambiguously specify biological resources. Having met the above requirements, in future, SWT will receive wide adoption with in systems driven research community. The reason lies in practical difficulties implementing such mechanisms to extract meaningful knowledge from raw integrated data. Very few recent projects have tried to leverage the capabilities of inference technology. The RDFScape Splendiani, , is one of the few recent work in life sciences domain, which has attempted to use reasoners program which can determine relations among ontology classes on BioPAX data inside Cytoscape Shannon et al.
In another novel study a different approach using Semantic Web methodologies to integrate gene data with phenotype data was demonstrated.
Hierarchical Biological Pathway Data Integration and Mining
It used RDF graph network analysis with reasoners to prioritize candidate cardiovascular disease genes Gudivada, However all the projects that have used inference technology are tried on the data integrated from limited number of resources, but not on Web-scale datasets. Ideally where RDFS and OWL constructions are used, it should be possible to apply automated reasoning over data schema and innovate meaningful knowledge.
However at present Semantic Web is not completely ready to equip with inference engines. One of the potential reason is problems posed by large ontologies [e. It is currently unfeasible to retrieve, modify and process concepts at runtime as conceived for their utilization on Semantic Web.
Because current reasoners and other tools that support Semantic Web require that all the information that they process should be loaded into memory. This can severely curtail performance or even fail when scaled to large ontologies. Several algorithms have been proposed to decompose large ontologies into less manageable and meaningful pieces retaining some of the semantics of the full version. However multiple limitations still persist, requiring future research aimed in this direction.
In previous section Federated Databases and Web Services we discussed how Web services can help to develop federated systems that could keep pace with the rapid advances in systems research. But, numerous issues associated with Web services could hinder the progress. Issues related to maintenance of code that might affect the scalability and ease of development when Web services are built on SOA.
Newer software development paradigm like Aspect Oriented Programming AOP solves the problems associated with code-tangling and code-scattering Kiczales et al. But, adoption of AOP is yet to percolate into life science development stream. Ontologically described Web service interfaces are not yet completely available which need to be addressed for realization of automatic discovery of services. A limitation of WSDL and SOAP is it being purely syntactical cannot express the semantics of underlying data and services which renders them inaccessible by machine.
Adding semantics to represent the requirements and capabilities of Web services is essential for achieving unambiguity and machine interpretability. Work on automatic higher level integration of Web services and data by machine is in its incipient stage and progressing slow. The reason underlying slow implementation of such a useful infrastructure is: 1 it presupposes a presence of formal logic over Web resources i. Recently, WSDL-S semantic markup of Web services description language was proposed as an alternative solution to the problem Miller et al.
Adoption of Web3. The Web3. This means Web3. Conceptually in Web3.
Allowing structured information to be read by different programs across the Web and enabling users to do more accurate searches and finding precisely what they want. Scientific workflows are ideal for in silico experimentation in advancing systems research. Several of the workflow systems are significantly developed including the Taverna workflow workbench Oinn et al.
Workflows include number of master services described in WSDL file that coordinate or aggregate activities together. Some of the workflow can be highly scalable to span multiple domains and organizations dispersed in different geographical locations. In such a scenario user interactions with the workflows at several intermittent levels is preferable facilitating interactive steering and monitoring. This will give user, control over exception handling, monitoring data, and choosing alternative work paths steering depending on the results witnessed at runtime.
Workflow management will be especially crucial for computational intensive and long-running workflows and services which are typically encountered in in silico systems scale analysis. Further, Business Processes Enterprise Language BPEL was recently proposed; it has several key advantages to specify scientific workflows in a distributed computational setup Akram et al.
To succeed, systems research must be a collaborative, cross-disciplinary and a broad organizational endeavor similar to successful initiative like Alzforum Lam et al. Several tasks integral to systems research such as ontology development, URI standardization, developments of tools requires involvement of scientists from different backgrounds including biologist, physicians, computer scientist, mathematicians and statisticians.
To facilitate this type of multidisciplinary interaction, certain prevailing challenges must be met including: 1 adoption of machine-readable data representation formats including semantically aware formats; 2 workflows to address data quality and integrity; 3 implementation of resource identity; and 4 tracking of provenance and ownership. The vision of the Web2. Useful collaborative Web tools and applications like wiki, blogs, mashups, and light weight Web apps for integration of distributed Web resources on demand will be made available for systems driven research community fostering active participation and an opportunity to take advantage of its integrative and analytical potential.
We have discussed the current state of the art approaches and technologies and open issues of database and Web application implementation in context of systems driven research. First we provided issues associated with the data integration and then we discussed how these issues have been tackled.
And, finally, we discussed the corresponding open issues and their possible solutions. Despite considerable progress in appropriate technologies and efforts to establishing an efficient computational platform, the integration of biological data to meet systems driven research will remain a challenging problem for both present and conceivable future. We need to stay attuned to three important aspects that drive the field: science, technology and society. Only by a consorted effort and support by all players of research community like database providers, funding agency, experimental and theoretical biologist, we will be able to bring revolution in systems driven research.
To this end selecting and implementing the most appropriate technology is of paramount importance.
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. Abramson, D. High-throughput cardiac science on the Grid. A Math.
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Web Service Mining Application To Discoveries Of Biological Pathways
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